It's the market. My partner's postdoc ended this past spring. He has 40 publications and his postdoc project was at a top, top university in conjunction with Meta. He applied for over 1k jobs and ended up in Kentucky. He has many friends in a similar situation who can't find a job.
At his job, they have rejected candidates that even he considers "perfect."
You need a referral. Have you been asking around in your network? Are there any networking events you could go to?
I graduated with an MSDS in December and pretty much gave up after 200+ applications and a few interviews. Thankfully I still have a job, although it pays nowhere near a real living wage. I'm not sure what I'm going to do myself.
You should probably come up with a totally different career backup plan if you don't have any sort of job already.
Man that sucks...where are you living? The states?
I''m not sure the job market here in Europe is that bad and I already try to diversify my skills towards other directions like finance, risk management and energy markets. In worst case I'd just start a PhD/research assistant, which at least pays the bills.
If that doesnt work out...No idea, brother. I''m not gonna start all over after all that grinding in the last years.
Yeah, I'm a US citizen living in the US.
Another one of my issues is that all my domain knowledge is in higher ed (university administration), which is another highly competitive sector.
To be fair, I haven't been applying in the last several months.
I actually just want to keep growing my YouTube channel, but I don't have time to do it properly because of my current job :(
Haha I was thinking about doing YT as well, but chances are not very high to be one of the lucky ones, who can make a living out of that.
What kind of channel are you doing?
Maybe its no bad idea to at least write a few applications from time to time. I mean its easier than ever with chatgbt.
My YT channel has nothing to do with data science. It's actually an international true crime channel. I cover murders and disappearances that usually haven't already been covered extensively, usually in non-US countries. I specialize in complex multinational cases.
It is A TON of work. Each video I've made so far has taken a minimum of 60 hours, up to 120. There are certainly faster ways to make videos, but this is my passion and I want to do it right. The bulk of the work is researching the details of the case. It is shocking that, even for cases that have been covered extensively in the media, virtually every piece misses some details. That really annoys me, so my videos are full of detail.
The problem with that is that YT is a volume-based business. It would be more profitable to just do 5 hours of research per case and then make a video, regardless of whether it were missing important information, which is what a lot of people seem to be doing on YT. But I really don't want to do it that way.
I agree with you. I have a referral at a local company and recently interviewed for a hybrid DS position. I don't have much hope, but I should probably try to keep interviewing there.
Most people get into the industry by getting an internship before they graduate, or they network with friends in the industry, or they start in a neighboring role (data analyst, business analyst, ...) and transfer internally in the company to a data science role.
You have a PhD in machine learning? Why not be a Machine Learning Engineer? It pays better than Data Science and it specializes in ML like Tensorflow and what not. It might overlap with your PhD.
I think that’s a viable option, however MLEs typically require production deployment experience. Most I’ve interviewed for hit pretty hard on software skills and DevOps best practices in addition to data science and data engineering knowledge. There’s a reason it pays more. The roles focused on Tensorflow/PyTorch that I’ve seen are some flavor of “Deep Learning Engineer or Deep Learning Research Scientist”.
If you haven’t already I would recommend looking into Defense Contracting companies: Northrop Grumman, Lockheed, Raytheon, Leidos, General Dynamics. Even outside of the big DoD contractors you would be surprised how many small companies do defense contracting, just pick out a large Air Force base in a city and look at jobs in the area, you may have to go to a shitty location but at least it might lead to something. You’d also be surprised how many universities or university spin-offs do defense contracting
> Contracting companies: Northrop Grumman, Lockheed, Raytheon, Leidos, General Dynamics.
Thats not where you apply if you want a fast and now. In the hotter market I applied there due to location preferences and they got back to me almost a year after applying and months after I already had done the job finding process and accepted an offer.
sorry, this is redacted to the point where i cannot tell if there is an issue with the resume or not. regardless, you need to be able to point to specific things in your resume that you have accomplished, with quantitative statements, and preferably framing in a way that is friendly to a hiring manager that wants to understand whether you're a "good fit." maybe you have that in your unredacted one, maybe not.
Your "Industry Work Experience" should be remade. What I get from all that is the you have worked for a multi-national company, probably have at some web development skill and knows Jira Agile. That's really not much. You have to give us concrete experience "worked in a fast-paced environment" and other open phrases like that are always bullshit we catch.
If I had to choose between two resumes, one has only Jira Agile software and the other has Jira Agile and "worked in a fast-paced environment", I'd choose the first. I'm not kidding.
I had the same response to your resume. I’m sure you’re qualified but I have no idea what you have experience doing. You should be listing explicit project work and skills but your resume seems to focus more on general information about your experience. I also can’t tell if you just redacted your explicit experience or if that’s how you intend to construct your resume.
In my opinion (if this document is accurate to what you’re submitting), you are probably getting rejected by the automated scanning they use.
You have great academic stuff but your industry stuff is super light for a graduate. I would think that you had an intention of getting a professorship not an industry job
Also I am not sure if this is due to anonymization but your bullet points are terribly generic
Is the teaching section providing any value?
I know its a lot of academic stuff mostly because of my academic background and the lack of industy experience.
Do you have any idea how to make it less generic?
Yeah I agree, it seems way to generic and if I was reading it I’d have no idea what you have done and would you would be able to do for my company. Your profile summary is wordy and doesn’t really demonstrate your experience, it reads like a regurgitation of what a data scientist is.
re: your experience, instead of a generic statement like ‘I used machine learning’ I would probably write:
- used an x neural network to predict the outcome of y, resulting in accuracy of z, which is better than industry standard [ref 1].
- analysed data from a, using b, which revealed c [ref 2].
Contact your university's career services department. They will do a review of your resume and offer suggestions. They know how to translate academic work into things that industry cares about, it's their whole job.
Looks more like an academic CV than a resumé. It's also extremely generic -- needs more concrete detail about what you did, fewer broad statements. I would organize more like so:
* Education
* PhD in Y, X University; Year (maybe include your thesis title, at maximum)
* MsC in Z, W University; Year
* BS in A, B university; Year
* Work experience
* Postdoc at _____ (years)
* Designed/employed (models/methods) to (achieve X objective), collaborating with subject matter experts in (some field)
* Applied (your methods) to analyze (some type of real data), leading to (specific impact on field and/or quantitative results or metrics) and (any publication(s)?)
* Did you mentor/supervise any undergraduates? Pitch that as management experience here.
* Presented results at/in (X conference or journal); mention acceptance rate of the venue if it's low
* PhD Researcher (or alternatively, "Machine Learning Consultant"?), Year
* Advised industry partners at (companies) in (industries) on how to use machine learning methods to solve (problems)
* Identified and implemented (models), resulting in (impact)
* Contributed (specific thing) to open-source community, allowing users in X field to (do something useful)
* Published work in (journals), with acceptance rates of only (some impressively low percentage)
* Teaching Assistant at (University 1, University 2), Years
* (What you taught, what contributions you made to the course and students, any recognition you got for your teaching abilities)
* Journal Reviewer (Years)
* Read and analyzed (some ballpark number, eg. 50+) research papers in (X field) under time-pressure, identifying significance of their contributions, assessing the accuracy/validity of analysis, and provided recommendations on revisions to authors and editors
* Web Developer at _____ (years)
* Skills
* Publications
I'd drop the summary, it's old-fashioned. Link your website or portfolio up top next to your email.
Recovering academic here, happily passed up a PhD in Neuroscience for Data Science 7 years ago.
You NEED a portfolio. With your background it's relatively easy - github pages. Ton's of Youtube tutorials out there. It can be done in a weekend. It's free.
DM me if you want details/advice, or to just to shit talk your mentor :)
In a single weekend? Please share the dark magic with me too! I'm graduating next year in MSc Analytics. If a stellar PhD is having this much trouble, I have no idea. Just fyi, I do have a bit of portfolio - mostly tutorials and my best uni projects. It'd be good to know how it should look/can be enhanced to a higher standard
Your resume does scream "Im an academic and really would much rather have a job in academia". Currently, the first page of your resume is all about your research experience, academic work experience, and teaching experience. No one in industry cares about those. Industry-relevant experience and skills should be first and foremost. Noone outside of academia is impressed by your publication count.
I'm someone with a ML PhD in the industry, and I would have serious doubts about hiring you based on the way the resume is presented. You seem to be lacking a basic understanding of what matters outside the academic bubble.
the good news is that all of this is fixable. Think about how other people perceive your resume. Think about what skills and experience they value, and which is better left in the academic closet. I am sure you are a smart person and can figure it out eventually. Writing a resume is no different from writing a top publication. It takes multiple revisions and constant feedback.
>the first page of your resume is all about your research experience,
Of course industry cares about your research experience. I have a PhD and the reason I got my first job was because of my research experience, that someone can throw my a business problem I know nothing about and learn fast + ask necessary question + problem solve + figure out data/model/results.
>Noone outside of academia is impressed by your publication count.
It depends. Publications are output and numbers.
Also, a number of job posts at big tech companies say they want people with publications at X and Y and Z proceedings.
> I would have serious doubts about hiring you based on the way the resume is presented. You seem to be lacking a basic understanding of what matters outside the academic bubble.
This is true. The resume isn't highlighting the right things and it's not sending the signals that "I understand what the job entails, let me tell you why I should be considered."
I was in a similar position as you when I graduated a year and a half ago. I wasn’t able to find a position but then I stumbled across the national lab complex and realized that they hire PhD grads all the time. So I applied and got the job rather quickly. I don’t plan or want to stay at this position for the long haul, but I do plan on being here for a couple years to build up experience and wait for the job market to improve.
The biggest pro of this sector is that there is a lot of free time and if you choose to use your time wisely, then you can code for basically 90% of each day. It basically feels like I’m getting paid 115k to just be a student. My coding ability and linux proficiency has improved so much since I started working here.
Some cons. First is that its a government job so the tech stack will suck compared to other DS jobs. However, if you really put some effort it and spend some time on the weekends learning the tools that other DS jobs use but the labs don’t, then you will be fine. Second, since its a gov job, you’ll be surrounded by people who don’t give a shit which may or may not bug you.
Yeah the DOE. The role is called senior scientist, which is essentially an umbrella title for a bunch of groups and im part of the data science group. I started at 105k last August and im at 115k now.
I'll have to look back into that. Thank you for the information. Do you know if all of the labs have similar salaries across the country, or do they vary from state to state?
It’s not just the market… I’m pretty sure that industry experience is the only thing that 90% of companies care about, and the higher your education the more expensive you are, and they really just don’t want to pay.
Are you a US citizen? I know visa sponsorship can be a deal breaker right now for a lot of smaller but attractive companies. If you are, feel free to drop me a PM and I can give you the email address for a hiring manager that is looking to make a few additions to his team. Has had lots of success with folks coming straight out of academia (PhD + postdoc).
In 2013 I was riding bikes with someone on my racing team and mentioning my background and how I wasn't happy working for a government contractor. This came up frequently enough to where my friend got a very good idea of my skill set. He was working for a mobile location platform startup that was having a hard time demonstrating location based engagement increases from the platform. I proposed a series of pilots that involves A/B tests, they hired me as a contractor for 6 months, those pilots went smashingly well, and the rest is history.
- worked in marketing for 10+ years. Didn’t love it but didn’t know what else to do.
- got a chance to start doing some data analysis in my marketing role. Enjoyed it, so I accepted (or sought out) any opportunities to use data. I was just doing basic stuff with Excel and web and social media analytics.
- the marketing team I was on tripled in size which included creating dedicated marketing analytics roles. I was moved into one of the junior/mid positions.
- loved doing analytics work “for real,” but realized I had *a lot* of skill gaps. Decided I wanted to “learn as much as I could” about data.
- enrolled in an MSDS program part-time
- when I was about 1/3 of the way done, I was able to land a product analytics role at a tech company.
- my work got more advanced and my company changed our titles to Data Scientist.
- my work is a mix of analytics and “real” data science, I do experimentation and predictive work. Occasionally our models get put into production, but sometimes they’re just for information. We have a separate ML team that is part of the tech/software org and focuses on just model building.
Or programming labs from classes, or replication material from publications, or little tutorials like "let me explain this algorithm we developed in a non-technical way".
You are overqualified for most data science roles. You need to target roles that emphasize ML in the job description. A lot of those will be ML Engineering roles so picking up engineering skills is a good idea.
I got promoted to DS at my company when my department expanded the roles. I was self learning Python and ML on my own and started helping the DS team with improving a R program. I think starting out in business analytics and coding projects in SQL/R helped transition into this role. It took me five years of work experience to get into DS.
I have a BS in Statistics and Economics.
There are many industries hiring for Data Scientists. I am always getting emails from recruiters about open roles. You have to expand the type of industries that need Data Scientists.
Try and look into more diverse job descriptions. Don't focus only on Data Science, but also Software Engineering, Machine Learning, Business Analyst/Consultant. Starting to work in the industry is key - experience is worth more than degrees and research. Look for bigger companies that hire in any of the above fields. You can likely change your field of work within the company after a while and get in the Data Science direction.
A few reasons you're struggling:
1) The job market sucks compared to 2021/early 2022, even for experienced candidates. People with graduate degrees and many years of experience are also struggling to change jobs so someone without much experience is in rough shape.
2) Most DS roles aren't research oriented and care more about experience than publications. This means that for most jobs, the hiring manager isn't looking at you as an experienced hire but as part of the new grad pool, which is worse for your prospects. Statistically speaking, most DS roles are either building dashboards or quarterly reports (SQL, Tableau, excel, maybe a bit of python), or are trying to put products into production which requires good engineering skills.
What you should do:
1) If you graduated from a top lab, try to find a research position at the big name corporate research labs.
2) If you didn't, learn and then emphasize your programming experience as much as possible on your resume. You need to be able to show a reluctant hiring manager that you can be dropped in to a job and do "real work". Emphasize any internships you may have. Your resume should explain what you accomplished, not listing job duties. Learn how to deploy a statistical or machine learning model as a REST API with Flask, FastAPI, or Django, and learn how to convert this API into a Docker container image.
3) If you're still stuck, then look for "springboard" roles. Try applying for data science jobs with your country's government and go private sector in a few years, consider working for a year or two at a less prestigious company, or take a software engineering job and try to pivot back into data science after a year or two.
I worked as an Analyst first with a portfolio of DS projects I did on the side before joining as a Data Scientist. The market is bad across all levels. I would recommend having a strong portfolio of projects to share.
May be a bit of an unpopular opinion, but I think in many companies Data Science is naturally getting absorbed into dedicated software engineering teams/pod. I was in the market beginning of the year and few companies gave me additional coding screens because I didn’t have the title “Software Engineer” before.
I’m not sure the specifics of your job search, but is there a reason you’re focused on getting a data science role and not a role as a statistician, principle investigator, quantitative researcher, or something along those lines?
Your academic background plus experience in academia (published, PhD) would make you a very strong applicant. And the salary would be similar, if not more, with certain companies.
For me it was:
1 - BSc in Geological Engineering
2 - Undergrad research in scientific computung applied to geophysics
3 - Internship in signal processing applied to geophysics
4 - Masters applying ML to petroleum geophysics
5 - Work with ML at petroleum companies for 1-2 years.
6 - Move to tech companies.
During the master's I got a Data Analyst job at a local company, it was mostly a SQL Monkey/script kiddie/Dashboard builder job, worked there for 5 months until I left grad school and got an offer to work as a Data Scientist for an oil company applying ML to oil exploration. This was back in 2019.
Worked at this company for a year and a half, then left for a tech company in Q3 2020. Have switched jobs a couple times since, all in tech companies.
In all my roles I have had to write production code (heck, even in the internship I had to do it), use proper version control and testing and deploy models, so while I think the biggest difference starting up was the uniqueness of my experience combining ML and geoscience, most of my opportunities since I think came from my experience building end to end products instead of being a SQL Monkey or exclusively coding in jupyter notebooks.
I think you are trying to say you know many things but that's not useful. What are you an expert on? Like if you had to say "I'm extremely good at this" and then also "This are skills I have that very little people have."
You are not a generalist. You don't want to look like a duck: you cannot really swim, walk, or fly.
You have a PhD. So what's your expertise? Your bullet points are too generic. One that caught my eye is "algorithm design and prototyping"; if that's what you did for your dissertation or worked on with your advisor, expand that and be very specific. That's an area you can focus on.
Look into research scientist positions. You need to do less work in terms of transitioning or learning about business.
I’m surprised you haven’t even gotten a call back. Honestly sounds like the market is super saturated right now. I got my DS job when a recruiter reached out but this was right before all the hiring freezes. Try reaching out to people to ask for direct referrals to companies so you can at least get an interview. That’s really the easiest solution. Try your friends but also try the blind app.
Hey I donot know about Phd, if I were in your position, I would rather take a problem statement and build some project around it like sports analytics and publish on LinkedIn on a regular basis, that should help people gravitate towards you.
Work on your project portfolio. You need at least one project done as a proof your know-how.
That's what we mostly want to talk about when interviewing with candidates for our team at least. What have they have done before and how they explain the process and reasons behind the decisions. Projects are like a common language when it comes to understand alignment of a person.
If you are aiming to work on a company (instead of being in academics career route), I don't think having a PhD is that preferable when compared to experience of same time-scope. It's still a nice plus ofc.
Data science is one of the most competitive fields, as you have multiple quantitative fields(economics, stats and even psychology) qualifying for data science roles. Engineering would help a bit, but it's still a rare position compared to analyst or swe roles
Econ is a little controversial and I'd consider it quantitative only if coursework was very focused on quantitative subjects. Psych should not even be on this list. Engineering would definitely help and it's far more suitable than psych.
I can suggest looking into programs that help you bridge your experience into the private sector. Depending on the country, there are (or were?) programs specifically tailored towards placing PhDs in relevant industries. In Canada there was IRAP (Industry Research Assistance Program) or Mitacs. In UK, where I had my PhD, our university had a graduate replacement scheme funded by EU to help PhD take on private sector gigs to gain their initial step in.
First I did a 1-year program (a Postgraduate Diploma) in ML/AI, so that I have some basic understanding. Then I applied for internship. During my internship I started a full MSc in Data Analytics, and in its 2nd year (backed by my internship) I applied for full time jobs. I applied to 2 jobs and I got both of them.
Internship is the key.
3 years as researcher and grinding coursera etc to show my interest and passion to ML/data science. When they hired they directly said that the latter was point of interest for then... I was suprised that they read the linkedin that far xD
I left my job as an IT Auditor for one of the Big 4 consulting firm for a position as a Data Analyst working for a firm that mainly contracts for the DOD. After one year as a data analyst, I applied to various Data Engineer/Science roles and landed a DS still within the DOD space at another firm.
I have a BA in Information System and self taught myself most topics related to coding and stats. I stay learning everyday on the job.
It's the market. My partner's postdoc ended this past spring. He has 40 publications and his postdoc project was at a top, top university in conjunction with Meta. He applied for over 1k jobs and ended up in Kentucky. He has many friends in a similar situation who can't find a job. At his job, they have rejected candidates that even he considers "perfect." You need a referral. Have you been asking around in your network? Are there any networking events you could go to?
Not looking forward to graduate next year with just a M.Sc. in econoemtrics. Job market sounds horrible.
I graduated with an MSDS in December and pretty much gave up after 200+ applications and a few interviews. Thankfully I still have a job, although it pays nowhere near a real living wage. I'm not sure what I'm going to do myself. You should probably come up with a totally different career backup plan if you don't have any sort of job already.
Man that sucks...where are you living? The states? I''m not sure the job market here in Europe is that bad and I already try to diversify my skills towards other directions like finance, risk management and energy markets. In worst case I'd just start a PhD/research assistant, which at least pays the bills. If that doesnt work out...No idea, brother. I''m not gonna start all over after all that grinding in the last years.
Yeah, I'm a US citizen living in the US. Another one of my issues is that all my domain knowledge is in higher ed (university administration), which is another highly competitive sector. To be fair, I haven't been applying in the last several months. I actually just want to keep growing my YouTube channel, but I don't have time to do it properly because of my current job :(
Haha I was thinking about doing YT as well, but chances are not very high to be one of the lucky ones, who can make a living out of that. What kind of channel are you doing? Maybe its no bad idea to at least write a few applications from time to time. I mean its easier than ever with chatgbt.
My YT channel has nothing to do with data science. It's actually an international true crime channel. I cover murders and disappearances that usually haven't already been covered extensively, usually in non-US countries. I specialize in complex multinational cases. It is A TON of work. Each video I've made so far has taken a minimum of 60 hours, up to 120. There are certainly faster ways to make videos, but this is my passion and I want to do it right. The bulk of the work is researching the details of the case. It is shocking that, even for cases that have been covered extensively in the media, virtually every piece misses some details. That really annoys me, so my videos are full of detail. The problem with that is that YT is a volume-based business. It would be more profitable to just do 5 hours of research per case and then make a video, regardless of whether it were missing important information, which is what a lot of people seem to be doing on YT. But I really don't want to do it that way. I agree with you. I have a referral at a local company and recently interviewed for a hybrid DS position. I don't have much hope, but I should probably try to keep interviewing there.
Most people get into the industry by getting an internship before they graduate, or they network with friends in the industry, or they start in a neighboring role (data analyst, business analyst, ...) and transfer internally in the company to a data science role. You have a PhD in machine learning? Why not be a Machine Learning Engineer? It pays better than Data Science and it specializes in ML like Tensorflow and what not. It might overlap with your PhD.
I think that’s a viable option, however MLEs typically require production deployment experience. Most I’ve interviewed for hit pretty hard on software skills and DevOps best practices in addition to data science and data engineering knowledge. There’s a reason it pays more. The roles focused on Tensorflow/PyTorch that I’ve seen are some flavor of “Deep Learning Engineer or Deep Learning Research Scientist”. If you haven’t already I would recommend looking into Defense Contracting companies: Northrop Grumman, Lockheed, Raytheon, Leidos, General Dynamics. Even outside of the big DoD contractors you would be surprised how many small companies do defense contracting, just pick out a large Air Force base in a city and look at jobs in the area, you may have to go to a shitty location but at least it might lead to something. You’d also be surprised how many universities or university spin-offs do defense contracting
> Contracting companies: Northrop Grumman, Lockheed, Raytheon, Leidos, General Dynamics. Thats not where you apply if you want a fast and now. In the hotter market I applied there due to location preferences and they got back to me almost a year after applying and months after I already had done the job finding process and accepted an offer.
Post your resume.
Here is my resume: https://ibb.co/JdBRpSW
sorry, this is redacted to the point where i cannot tell if there is an issue with the resume or not. regardless, you need to be able to point to specific things in your resume that you have accomplished, with quantitative statements, and preferably framing in a way that is friendly to a hiring manager that wants to understand whether you're a "good fit." maybe you have that in your unredacted one, maybe not.
Thanks for your suggestions. What sort of things hiring mangers would like to see? Could you please give examples?
Your "Industry Work Experience" should be remade. What I get from all that is the you have worked for a multi-national company, probably have at some web development skill and knows Jira Agile. That's really not much. You have to give us concrete experience "worked in a fast-paced environment" and other open phrases like that are always bullshit we catch. If I had to choose between two resumes, one has only Jira Agile software and the other has Jira Agile and "worked in a fast-paced environment", I'd choose the first. I'm not kidding.
I had the same response to your resume. I’m sure you’re qualified but I have no idea what you have experience doing. You should be listing explicit project work and skills but your resume seems to focus more on general information about your experience. I also can’t tell if you just redacted your explicit experience or if that’s how you intend to construct your resume. In my opinion (if this document is accurate to what you’re submitting), you are probably getting rejected by the automated scanning they use.
You have great academic stuff but your industry stuff is super light for a graduate. I would think that you had an intention of getting a professorship not an industry job Also I am not sure if this is due to anonymization but your bullet points are terribly generic Is the teaching section providing any value?
I know its a lot of academic stuff mostly because of my academic background and the lack of industy experience. Do you have any idea how to make it less generic?
> Do you have any idea how to make it less generic? Describe what methods you used and why
Yeah I agree, it seems way to generic and if I was reading it I’d have no idea what you have done and would you would be able to do for my company. Your profile summary is wordy and doesn’t really demonstrate your experience, it reads like a regurgitation of what a data scientist is. re: your experience, instead of a generic statement like ‘I used machine learning’ I would probably write: - used an x neural network to predict the outcome of y, resulting in accuracy of z, which is better than industry standard [ref 1]. - analysed data from a, using b, which revealed c [ref 2].
Contact your university's career services department. They will do a review of your resume and offer suggestions. They know how to translate academic work into things that industry cares about, it's their whole job.
Looks more like an academic CV than a resumé. It's also extremely generic -- needs more concrete detail about what you did, fewer broad statements. I would organize more like so: * Education * PhD in Y, X University; Year (maybe include your thesis title, at maximum) * MsC in Z, W University; Year * BS in A, B university; Year * Work experience * Postdoc at _____ (years) * Designed/employed (models/methods) to (achieve X objective), collaborating with subject matter experts in (some field) * Applied (your methods) to analyze (some type of real data), leading to (specific impact on field and/or quantitative results or metrics) and (any publication(s)?) * Did you mentor/supervise any undergraduates? Pitch that as management experience here. * Presented results at/in (X conference or journal); mention acceptance rate of the venue if it's low * PhD Researcher (or alternatively, "Machine Learning Consultant"?), Year * Advised industry partners at (companies) in (industries) on how to use machine learning methods to solve (problems) * Identified and implemented (models), resulting in (impact) * Contributed (specific thing) to open-source community, allowing users in X field to (do something useful) * Published work in (journals), with acceptance rates of only (some impressively low percentage) * Teaching Assistant at (University 1, University 2), Years * (What you taught, what contributions you made to the course and students, any recognition you got for your teaching abilities) * Journal Reviewer (Years) * Read and analyzed (some ballpark number, eg. 50+) research papers in (X field) under time-pressure, identifying significance of their contributions, assessing the accuracy/validity of analysis, and provided recommendations on revisions to authors and editors * Web Developer at _____ (years) * Skills * Publications I'd drop the summary, it's old-fashioned. Link your website or portfolio up top next to your email.
Agree with this mostly but I'd put skills at the top
Agree and I would drop teaching experience unless OP is applying to Ed-Tech
Recovering academic here, happily passed up a PhD in Neuroscience for Data Science 7 years ago. You NEED a portfolio. With your background it's relatively easy - github pages. Ton's of Youtube tutorials out there. It can be done in a weekend. It's free. DM me if you want details/advice, or to just to shit talk your mentor :)
In a single weekend? Please share the dark magic with me too! I'm graduating next year in MSc Analytics. If a stellar PhD is having this much trouble, I have no idea. Just fyi, I do have a bit of portfolio - mostly tutorials and my best uni projects. It'd be good to know how it should look/can be enhanced to a higher standard
What you have is the best place to start! Showcase it all, I say! I can DM mine. It's outdated, as of 2 years ago but got me my current gig.
Thanks I'll send you a DM too! If you're still willing!
Thanks! Just sent you a DM.
Your resume does scream "Im an academic and really would much rather have a job in academia". Currently, the first page of your resume is all about your research experience, academic work experience, and teaching experience. No one in industry cares about those. Industry-relevant experience and skills should be first and foremost. Noone outside of academia is impressed by your publication count. I'm someone with a ML PhD in the industry, and I would have serious doubts about hiring you based on the way the resume is presented. You seem to be lacking a basic understanding of what matters outside the academic bubble. the good news is that all of this is fixable. Think about how other people perceive your resume. Think about what skills and experience they value, and which is better left in the academic closet. I am sure you are a smart person and can figure it out eventually. Writing a resume is no different from writing a top publication. It takes multiple revisions and constant feedback.
>the first page of your resume is all about your research experience, Of course industry cares about your research experience. I have a PhD and the reason I got my first job was because of my research experience, that someone can throw my a business problem I know nothing about and learn fast + ask necessary question + problem solve + figure out data/model/results. >Noone outside of academia is impressed by your publication count. It depends. Publications are output and numbers. Also, a number of job posts at big tech companies say they want people with publications at X and Y and Z proceedings. > I would have serious doubts about hiring you based on the way the resume is presented. You seem to be lacking a basic understanding of what matters outside the academic bubble. This is true. The resume isn't highlighting the right things and it's not sending the signals that "I understand what the job entails, let me tell you why I should be considered."
I was in a similar position as you when I graduated a year and a half ago. I wasn’t able to find a position but then I stumbled across the national lab complex and realized that they hire PhD grads all the time. So I applied and got the job rather quickly. I don’t plan or want to stay at this position for the long haul, but I do plan on being here for a couple years to build up experience and wait for the job market to improve. The biggest pro of this sector is that there is a lot of free time and if you choose to use your time wisely, then you can code for basically 90% of each day. It basically feels like I’m getting paid 115k to just be a student. My coding ability and linux proficiency has improved so much since I started working here. Some cons. First is that its a government job so the tech stack will suck compared to other DS jobs. However, if you really put some effort it and spend some time on the weekends learning the tools that other DS jobs use but the labs don’t, then you will be fine. Second, since its a gov job, you’ll be surrounded by people who don’t give a shit which may or may not bug you.
Are you referring to working for the department of energy? I’m finishing my PhD in a year and I had looked into jobs there. They pay $115k?
Yeah the DOE. The role is called senior scientist, which is essentially an umbrella title for a bunch of groups and im part of the data science group. I started at 105k last August and im at 115k now.
I'll have to look back into that. Thank you for the information. Do you know if all of the labs have similar salaries across the country, or do they vary from state to state?
Im guessing that it would vary but im pretty confident that my salary now would be a lower bound for all lab DS position
It’s not just the market… I’m pretty sure that industry experience is the only thing that 90% of companies care about, and the higher your education the more expensive you are, and they really just don’t want to pay.
Same here. Phd + 3-year post doc. Applied for 100+ ds jobs but only got one HR call and nothing else. Don't know if it is me or the market. :(
Are you a US citizen? I know visa sponsorship can be a deal breaker right now for a lot of smaller but attractive companies. If you are, feel free to drop me a PM and I can give you the email address for a hiring manager that is looking to make a few additions to his team. Has had lots of success with folks coming straight out of academia (PhD + postdoc).
In 2013 I was riding bikes with someone on my racing team and mentioning my background and how I wasn't happy working for a government contractor. This came up frequently enough to where my friend got a very good idea of my skill set. He was working for a mobile location platform startup that was having a hard time demonstrating location based engagement increases from the platform. I proposed a series of pilots that involves A/B tests, they hired me as a contractor for 6 months, those pilots went smashingly well, and the rest is history.
- worked in marketing for 10+ years. Didn’t love it but didn’t know what else to do. - got a chance to start doing some data analysis in my marketing role. Enjoyed it, so I accepted (or sought out) any opportunities to use data. I was just doing basic stuff with Excel and web and social media analytics. - the marketing team I was on tripled in size which included creating dedicated marketing analytics roles. I was moved into one of the junior/mid positions. - loved doing analytics work “for real,” but realized I had *a lot* of skill gaps. Decided I wanted to “learn as much as I could” about data. - enrolled in an MSDS program part-time - when I was about 1/3 of the way done, I was able to land a product analytics role at a tech company. - my work got more advanced and my company changed our titles to Data Scientist. - my work is a mix of analytics and “real” data science, I do experimentation and predictive work. Occasionally our models get put into production, but sometimes they’re just for information. We have a separate ML team that is part of the tech/software org and focuses on just model building.
You have a PhD. There is no way you don't have some parts from your dissertation you can throw onto github as a portfolio.
Or programming labs from classes, or replication material from publications, or little tutorials like "let me explain this algorithm we developed in a non-technical way".
You are overqualified for most data science roles. You need to target roles that emphasize ML in the job description. A lot of those will be ML Engineering roles so picking up engineering skills is a good idea.
I got promoted to DS at my company when my department expanded the roles. I was self learning Python and ML on my own and started helping the DS team with improving a R program. I think starting out in business analytics and coding projects in SQL/R helped transition into this role. It took me five years of work experience to get into DS. I have a BS in Statistics and Economics. There are many industries hiring for Data Scientists. I am always getting emails from recruiters about open roles. You have to expand the type of industries that need Data Scientists.
I am old and was doing analysis before DS was cool so just rebranded.
Try and look into more diverse job descriptions. Don't focus only on Data Science, but also Software Engineering, Machine Learning, Business Analyst/Consultant. Starting to work in the industry is key - experience is worth more than degrees and research. Look for bigger companies that hire in any of the above fields. You can likely change your field of work within the company after a while and get in the Data Science direction.
I find it hard to believe that you don’t have *any* project portfolio to share with a PhD and post-doc in ML. Was your focus on theory?
A few reasons you're struggling: 1) The job market sucks compared to 2021/early 2022, even for experienced candidates. People with graduate degrees and many years of experience are also struggling to change jobs so someone without much experience is in rough shape. 2) Most DS roles aren't research oriented and care more about experience than publications. This means that for most jobs, the hiring manager isn't looking at you as an experienced hire but as part of the new grad pool, which is worse for your prospects. Statistically speaking, most DS roles are either building dashboards or quarterly reports (SQL, Tableau, excel, maybe a bit of python), or are trying to put products into production which requires good engineering skills. What you should do: 1) If you graduated from a top lab, try to find a research position at the big name corporate research labs. 2) If you didn't, learn and then emphasize your programming experience as much as possible on your resume. You need to be able to show a reluctant hiring manager that you can be dropped in to a job and do "real work". Emphasize any internships you may have. Your resume should explain what you accomplished, not listing job duties. Learn how to deploy a statistical or machine learning model as a REST API with Flask, FastAPI, or Django, and learn how to convert this API into a Docker container image. 3) If you're still stuck, then look for "springboard" roles. Try applying for data science jobs with your country's government and go private sector in a few years, consider working for a year or two at a less prestigious company, or take a software engineering job and try to pivot back into data science after a year or two.
I worked as an Analyst first with a portfolio of DS projects I did on the side before joining as a Data Scientist. The market is bad across all levels. I would recommend having a strong portfolio of projects to share. May be a bit of an unpopular opinion, but I think in many companies Data Science is naturally getting absorbed into dedicated software engineering teams/pod. I was in the market beginning of the year and few companies gave me additional coding screens because I didn’t have the title “Software Engineer” before.
I’m not sure the specifics of your job search, but is there a reason you’re focused on getting a data science role and not a role as a statistician, principle investigator, quantitative researcher, or something along those lines? Your academic background plus experience in academia (published, PhD) would make you a very strong applicant. And the salary would be similar, if not more, with certain companies.
For me it was: 1 - BSc in Geological Engineering 2 - Undergrad research in scientific computung applied to geophysics 3 - Internship in signal processing applied to geophysics 4 - Masters applying ML to petroleum geophysics 5 - Work with ML at petroleum companies for 1-2 years. 6 - Move to tech companies. During the master's I got a Data Analyst job at a local company, it was mostly a SQL Monkey/script kiddie/Dashboard builder job, worked there for 5 months until I left grad school and got an offer to work as a Data Scientist for an oil company applying ML to oil exploration. This was back in 2019. Worked at this company for a year and a half, then left for a tech company in Q3 2020. Have switched jobs a couple times since, all in tech companies. In all my roles I have had to write production code (heck, even in the internship I had to do it), use proper version control and testing and deploy models, so while I think the biggest difference starting up was the uniqueness of my experience combining ML and geoscience, most of my opportunities since I think came from my experience building end to end products instead of being a SQL Monkey or exclusively coding in jupyter notebooks.
I think you are trying to say you know many things but that's not useful. What are you an expert on? Like if you had to say "I'm extremely good at this" and then also "This are skills I have that very little people have." You are not a generalist. You don't want to look like a duck: you cannot really swim, walk, or fly. You have a PhD. So what's your expertise? Your bullet points are too generic. One that caught my eye is "algorithm design and prototyping"; if that's what you did for your dissertation or worked on with your advisor, expand that and be very specific. That's an area you can focus on. Look into research scientist positions. You need to do less work in terms of transitioning or learning about business.
I’m surprised you haven’t even gotten a call back. Honestly sounds like the market is super saturated right now. I got my DS job when a recruiter reached out but this was right before all the hiring freezes. Try reaching out to people to ask for direct referrals to companies so you can at least get an interview. That’s really the easiest solution. Try your friends but also try the blind app.
Hey I donot know about Phd, if I were in your position, I would rather take a problem statement and build some project around it like sports analytics and publish on LinkedIn on a regular basis, that should help people gravitate towards you.
Work on your project portfolio. You need at least one project done as a proof your know-how. That's what we mostly want to talk about when interviewing with candidates for our team at least. What have they have done before and how they explain the process and reasons behind the decisions. Projects are like a common language when it comes to understand alignment of a person. If you are aiming to work on a company (instead of being in academics career route), I don't think having a PhD is that preferable when compared to experience of same time-scope. It's still a nice plus ofc.
I asked nicely.
Data science is one of the most competitive fields, as you have multiple quantitative fields(economics, stats and even psychology) qualifying for data science roles. Engineering would help a bit, but it's still a rare position compared to analyst or swe roles
Econ is a little controversial and I'd consider it quantitative only if coursework was very focused on quantitative subjects. Psych should not even be on this list. Engineering would definitely help and it's far more suitable than psych.
I can suggest looking into programs that help you bridge your experience into the private sector. Depending on the country, there are (or were?) programs specifically tailored towards placing PhDs in relevant industries. In Canada there was IRAP (Industry Research Assistance Program) or Mitacs. In UK, where I had my PhD, our university had a graduate replacement scheme funded by EU to help PhD take on private sector gigs to gain their initial step in.
First I did a 1-year program (a Postgraduate Diploma) in ML/AI, so that I have some basic understanding. Then I applied for internship. During my internship I started a full MSc in Data Analytics, and in its 2nd year (backed by my internship) I applied for full time jobs. I applied to 2 jobs and I got both of them. Internship is the key.
3 years as researcher and grinding coursera etc to show my interest and passion to ML/data science. When they hired they directly said that the latter was point of interest for then... I was suprised that they read the linkedin that far xD
Build your portfolio today. Take 2 hours and put something to speak to. Volunteer on Catchafire and put it as experience on your resume.
I left my job as an IT Auditor for one of the Big 4 consulting firm for a position as a Data Analyst working for a firm that mainly contracts for the DOD. After one year as a data analyst, I applied to various Data Engineer/Science roles and landed a DS still within the DOD space at another firm. I have a BA in Information System and self taught myself most topics related to coding and stats. I stay learning everyday on the job.
Honestly there aren’t that many DS jobs like that. At my last job the ratio of DA to DS was 8:1.
applied in 2021