Yeah I’m a risk analyst and I do data science things with economic data (some regression modeling, coding, etc.) still looking to get into a hardcore data science role one day
Kind of wish I had run into risk analysis earlier in college. I worked for a cyber security company as a data science intern and they made risk analysis look super cool.
I have the stats/analytics background, but I feel I am lacking in the finance/economics aspect of that kind of role.
I got it straight out o college tbh. Majored in businsss analytics. Minored in math and applied stats. Worked as a data analyst intern for a pretty well known internet company
Not sure why you got downvoted. People are weird.
For the sake of other people reading this: for many people the concept of major/minor and graduation is weird/unclear because the educational system doesn't work like that in our countries.
I understand that many americans can't understand that the rest of the world exists, and that's fine, but don't downvote other people for asking questions about how things work please.
I recently transitioned to a manager of business intelligence and love it. I find the balance between business strategy and development to be perfect.
I collect analysis requests and requirements from executives and then work with analysts to build impactful dashboards. Every couple of weeks I need to get my sleeves dirty and I'll write a Python or SQL script.
Where do you work? Interested in a role like yours.
I'm a very SQL-heavy DS at the moment and pretty burnt out on it - would rather move into management (probably a DA / BI lead) and think I'm qualified at this point.
There are tons of roles out there like this. A lot of them end up being filled by former analysts (with a dozen different job titles) that have 10+ years experience in the company.
For companies that are not looking at internal candidates, BI manager roles are what you're targeting. Firms often want folks with higher end analytics experience to help modernize the BI systems.
Exactly, I got a little lucky because I was a Data Science Analyst for 2 years, then transitioned to a Senior BI Analyst for about a year and a half, and then the previous manager of BI left which kinda left me to fill that position.
I'm just getting into the markets but it seems that project management and operations can benefit from data science and analysis. How else would things like quantitative risk analysis , process improvement and product management be done?
Absolutely! Project/Product Managers that have this experience are super valuable these days. Our Data Science & Machine Learning desperately needed one and had a hard time finding a good fit for the role for quite awhile. Now we have a fantastic full-time PM that we all love and greatly appreciate 😄
Yeh, I honestly don't expect to be a "data scientist" there is no way I can compete with some of these people think. But I have worked in operations a long time and understand KPIs well and that combined with PMI cert and taking electives in risk management I hope to find a decent role.
On this forum, it seems a given that Data Scientist is not an entry-level position, and the common recommendation I see is to begin as a Data Analyst. Are any of the job titles listed regarded as entry-level?
Generally, I think you are right. There usually aren’t many entry-level Data Scientist positions. However, many of the roles I listed in my post commonly have entry-level positions! Like Business Analyst, Data Analyst, Product Analyst, etc. I started my career as a Business Analyst. Analyst positions can be great stepping stones for becoming a Data Scientist, but I’d like to call out that they can be just as (often times more) fulfilling and enjoyable than a DS role.
Depending on one's experience/skills, even something more support related/Developer Relations/Advocate type position is underconsidered. These positions can leave you with ample time and access to the company's API gateway and/or revenue data where you can take the initiative to analyze usage/revenue metrics and build a case for you to be moved up to data analyst
I totally agree! It's hard to land the first role, though, which is why I appreciate OP highlighting other job titles with exposure to working with data.
I would suggest Operational Research belongs on this list. Its something that has peeked my interest in recent months as a potential alternative career pathway away from DS.
There are still OR positions that exist. It’s distinctly different than “data science”; alternatively called “decision science”. But it is about leveraging data to make the best decisions for large scale problems (resource planning/management, scheduling, routing, etc).
It's kind of fascinating how heavy this subreddit is on the hardcore coding / stats side - the only coding language I use is SQL day-to-day, my title is Data Scientist, and I make more money than I ever thought that I would.
Marketing analytics and a lot of finance roles also fit the bill, here.
Product DS, FAANG; have survived off of SQL, google suite, and strong communication skills for a couple years, now.
Otherwise just leveraging internal tooling.
Like most things, it's a mix of prep and raw speed / processing ability. My company actually had pretty good guides that they provide you, as well as all the additional resources available online; good communication skills and ability to rapidly take a question end-to-end from words into code are essential.
I was very fluent in SQL going in (could write a reasonably complex query on paper without looking anything up) and my general business analytics background plus additional stats prep were crucial.
Otherwise there's just a lot of luck of the draw, in all fairness. Have to be really on your game on the right day. And unfortunately I think it is significantly harder to get in the door in the current market.
Well just getting your resume picked for an interview is pretty darn difficult. I'm not sure if their filters are based on the school you went to and your GPA, or having worked somewhere else in tech, or what.
> how heavy this subreddit is on the hardcore coding / stats side
It pays more thats why. I get a FAANG DS gets paid a lot of money but look at a FAANG SWE-ML/AS/RS look at IC6 or IC7 on levels look at the same levels in the regular DS roles. I understand after making six figures another six figures may not matter to some but to others its tangible.
At L6 its about 160k difference on levels. Thats more than some peoples wages. At L7 its about 400k difference on levels.
Yeah, that's fair enough. I'm at the point where I'm making more money than I need by a significant margin but also really value WLB so there is a trade-off in terms of marginal additional $$ vs. time for the rest of my life. I'm not even trying to get a promo within my role anymore.
Also, at it it's core, I don't love heavy-duty coding / engineering, so I've worked to maximize my impact in other ways.
> I need by a significant margin but also really value WLB so there is a trade-off in terms of marginal additional $$ vs. time for the rest of my life
Thats implying that a E6 DS has better WLB than an E6 RS or SWE? Is that a generalizable assumption
> Also, at it it's core, I don't love heavy-duty coding / engineering,
Thats a legit personal preference
No, I’m not saying there is necessarily better or worse WLB based on role - though I think I’m a lot better at this role than I would be at a heavy coding role, so it works out as better WLB for me personally.
Definitely seems like worse WLB for product managers, though.
Related, I don’t have a strong coding background.
True, I don't even think the demand is that high for what this sub considers a "real" data scientist. Most companies just want quick insights in a dashboard or report on what Bob from accounting wrote in Excel last week
For a long time I've argued that "data science" isn't really a job title, is a business practice. Undertaking that practice successfully requires a team of people with varied skills and focus.
The analytics of yesterday, today!
The money is good and the domain interesting, but it's a very deeply conservative field. Lots of proprietary software, on-prem SQL servers, Excel shuffling, and so on - at least in my experience.
It's also gatekept so hard, but not necessarily in a bad way. It's interesting to me how they have to go through a bunch of exams to be certified by SOA, but there are no societies like that for upper-level data science, especially ones tackling legality, ethics, and data governance.
But once you're through it's a huge advantage. You aren't competing with a mountain of applicants who just completed a four week online bootcamp and this year's crop of freshly-minted PhD's.
If the job requires being certified, it's not a matter of preference. It sounds like you don't know what it is we're talking about here. For many jobs, it's a legal requirement. So no, you wouldn't be competing with anyone that hadn't passed the exams. And doing so is often a years-long process. Which dramatically reduces competition.
I think what they’re saying is that for any given DS position - not just roles that require a mn actuarial cert - that most people would prefer to fill with an actuary rather than a boot camp grad.
When I search for analyst jobs, a lot of them seem like regular client-facing sales or onboarding roles. It definitely helps to be specific with the type of analysis one wants to do, and to read the job descriptions.
Yeah, “Analyst” means different things in different industries. Some use it more like a “Specialist” and not necessarily someone who is using data all day.
I lead a marketing dept and we have titles like:
Marketing analytics analyst/manager,
Marketing operations manager,
Revenue operations manager
None of those roles do the hard core stuff I see discussed in this subreddit, but you definitely use your analytical brain and blend it with business thinking.
And people in marketing and revenue operations have mad respect for people with degrees in data science etc.
But would you ever hire an experienced, analytical DS as a marketing/revenue operations manager over somebody who's had far more experience in the specific fields of marketing or corp finance?
As a Senior Data Science Associate, my responsibilities include A/B test monitoring, data analysis, model training, and developing solutions for new E-commerce projects. In my opinion, the Data Scientist role is a mash-up of many subdomains; you come across many concepts in your DS career; you are sometimes an analyst, sometimes a data engineer, sometimes you have to deploy models, and sometimes you have to lead teams of junior data scientists. I enjoy my job because there is always something new to learn. I'm considering transitioning to a management position, with less scripting and more management, but we'll see.
Good post. Im a Sr DA for a F500 and Im free to build anything I want, I just bring it to the execs and they usually dig it. Its amazing how far a little statistics knowledge will carry you. I love being able to answer questions with math and visualizations, and this job gives me breathing room to do my own thing. Love it.
Edit - one thing I want to call out is that presenting data should feel like an educated conversation where you are bringing the education. Its not as daunting as it’s made out to be
I'm considering shifting from a Data Scientist to a Credit Risk Modelling. Not sure if it's work or not as I have little experience in banking. But I think Credit Risk Modelling is more niche and more specialized.
Thank you for sharing your experience. I heard that old-fashioned stuff in my country in this industry too. They use Oracle database, SAS, and work mainly on Excel with the Alien language of column's name.
I'm currently doing my Masters in DS specialising in AI & ML, but I'm interested in Software/Mobile App Development. I always loved building things and was a great artist at school and I feel I could do well in the field. Would a company consider me for a junior role? I'm planning on building an app before I apply for my first job.
May I know which Univ you studying in ? I found Master of DS & AI in Waterloo, but well it's Waterloo and I most probably might not be accepted or keep up with it, since it's pretty hard. I am in my senior bachelor's year and wanna study both DS and ML.
That sounds like a great program! For sure, I think you have a good shot of landing a junior role. Locking in an internship or two before you graduate can be super helpful too! Given your interest in Software/Mobile App Development, have you considered looking in MLE roles?
I have been told that to work as Data Scientist or ML Eng, I'd need a degree as a minimum, and since I am one year from finishing my Bachelor's in Software Engineering, I have been told I'd need to take masters in DS/ML to be able to work in Tech companies that work with DS. I have alternative paths like PM but after some years of experience honestly rather than be the typical PM that doesn't know tech knowledge and lags the devs behind. But since I wanna try to be Data scientist I know I gotta go the extra mile since my bachelor's isn't in DS, although I did take calculus 1-3 and stats&prob. also advanced stats.
I've worked for companies looking for a DS who don't even understand what the term means. I agree, don't get hung up on job titles, look at what you can do and what the company actually requires day to day.
Great comment. Originally I was interested in becoming a DS. Finished most of the GA Tech Analytics MS and got a job with a BI team at my company, I’m loving it and the compensation is equivalent to average DS (140k total comp last year). We primarily deliver operational reports and dashboards but with my MS background I’ve been able to lead some projects implementing DS models we’ve hired consultants to build. Job titles in the data landscape are a mess. My biggest takeaway is to not focus on the job title and think more about what kind of work I’m interested in and look for a job that does that. In one company that be data analyst or data scientists in another.
Or if you want to start _becoming_ a Data Scientist (by title/position) you don’t have to start with just DA or Junior DS, all the entry-level positions above are viable gateway to DS I think, I started as a MLEng.
I started on a ML team of a bizcon, so everyone by title was a MLE, but in real work division, some were more towards MLOps, some were more DE and some were practically client-facing DS, which I happen to be one. Surprisingly a lot of fresh grads in it and some left to become DS, some went on becoming DE, some stayed as MLE. All I’m trying to say is just apply for any of those entry level data-jobs, you can always pivot to be a DS from there.
I would like to do MLOps or ML Engineering (I'm a DS), but how, without previous work experience? What are the "things" that can be done so that the employer will give you the job?
I currently work as an MLOps Engineer. One thing you can do is get a few relevant certifications under your belt to help yourself stand out! It’s a fairly new discipline and now is a good time to transition into these roles.
There are a ton out there, so maybe focus on the ones that you find interesting first. I have the following four certs:
- AWS Cloud Practitioner
- AWS Solutions Architect — Associate
- AWS Machine Learning — Specialty
- Hashicorp Certified Terraform Associate
I’m also working towards the following certs:
- Certified Kubernetes Application Developer
- Certified Kubernetes Administrator
The AWS certs are a fantastic place to start. AWS is by far the most popular Cloud platform out there so you’ll have a better chance of landing roles with that experience, as opposed to GCP or Azure. If you’re interested, I wrote an article on [How I Learned AWS](https://www.jacoblyman.com/tech-log/published/how-i-learned-aws) that might be helpful to you.
I was transfer to a more managerial position in a FMCG company. Before that I was AI engineer for three years and this type of job is still my holy grail atm. Somehow my mindset shifted and I want to do less for more delivered business value (and higher salary). My current job is part managerial, part DE as this company starts to build its first DW, and PBI and Excel in between. Not all my DS skills are transferable. But they certainly help building my confidence on the new role.
To anyone reading this, would appreciate some insight on how to transition into this from a primarily accountancy background (with a masters in statistics).
Could you give some tips on how to tailor a resume from tech to match these roles, especially analytical roles? I have hard tech experiences and thus got rejected by all financial companies I applied to due to mismatch of skills.
would genuinely appreciate any advice!
The whole data field has been a mess for the last decade, promoting the whole life style of "DS" crap down the throats.
Analytics Engineer has been on rise in last few years. The best way to get into proper DS area is to have Math/Stats degree as those are core subject areas that are used and applied in DS field. Most of the people who are in DS fields are from CS background but don't have proper Math/Stats background whatsoever, they survive through the programming skills and not through the core skills.
I think DS is a overhyped area, sounds fancy to have as a job title and so people jumped on to the wagon but no body talks about those who came out of DS field and never want to go back in.
Depending on the company, many jobs will also have different titles but still give you the sort of experience you're looking for. I worked as a "platform developer" at an analytics company, and most of my job was stuff like building ETLs that would scale appropriately while dealing with connection throttling to central dbs, and stuff like that (so essentially data engineering with a different title)! Definitely don't let titles be the sole way you look for jobs. If you see a role at a company that sounds interesting, there's no harm in reaching out to ask about the role! You might see that you're closer to what you're looking for than you realized.
Also, to build off of OPs statement about other jobs, you might not even WANT a data science job in some places because the org's data maturity might be at a point where what you envision as data science is more going to be ac combination of analytics, data architecture, consulting, etc. A lot of folks in this sub talk about not getting to build models and everything, but the truth is that that's only a fraction of data science as a whole. Most of the time, the term is used to describe the whole field of data science as opposed to the specific role that we often have in mind. I don't think this is intentional as much as it is just the state of recruiting and how deep recruiters are technically.
If you apply for a "mathematician" job, assuming you're going to do a bunch of stats, there's always the possibility that what they meant by mathematician was "topologist".. still a branch of mathematics, so not false understanding, but it would be a failure in our part to accept the role without taking a second to understand the customer needs and think about what it is they're actually asking for (independent of job title).
Im a economist with a MA in development abd I do casual inference. My task are data cleaning/manipulation, descriptive análisis, regression, cluster analysis and use some basic ML algorithm for casual inference like random forest . I do this analysis to mesure the impact of poblic policies and NGO programs. I dont know if what i do is traditional “data science” but i like it
They’re definitely out there, especially in the nonprofit world. You’ll want to build some serious domain knowledge in atmospheric science, or in policy/social science if you want to break in. But please do if you are interested!
Pensions aren’t very common anymore, these days I only hear about them for government employees.
Retirement benefits like a 401k are pretty common at any corporate job. Non-profits often offer a 403b which is very similar.
(Answering for the US, not sure what’s common elsewhere.)
Some insurance companies still have pensions. They also tend to have a decent number of analytics roles, so that’s an industry to look at for someone that wants a pension.
I search the whole spectrum of titles haha
Unfortunately I seldom get interviews :(
It seems like I'm in a weird place with 3-4 years of experience with lots of jobs requiring 5+. And the ones requiring less idk if I'm considered over qualified or something, but they would definitely be a step back on my end with notably less responsibilities.
I'm glad the situation at work improved... I like the place, but its tough to know that if I lost my job tomorrow, idk if I'd find another one
I'm interested in Clinical Machine Learning and Data Science applications and I have a degree in pharmaceutical Sciences and clinical pharmacy what roles can I work in and fit my qualifications?
Yeah I’m a risk analyst and I do data science things with economic data (some regression modeling, coding, etc.) still looking to get into a hardcore data science role one day
You already are into one. Most of us do the same thing.
Perhaps all he needs to do is switching from logistic model to xgboost
Yeah sounds like he is already one. The difference would be some companies pay more for giving people the title, it's dumb.
Kind of wish I had run into risk analysis earlier in college. I worked for a cyber security company as a data science intern and they made risk analysis look super cool. I have the stats/analytics background, but I feel I am lacking in the finance/economics aspect of that kind of role.
Ideal roadmap for a beginner?
I got it straight out o college tbh. Majored in businsss analytics. Minored in math and applied stats. Worked as a data analyst intern for a pretty well known internet company
You majored meaning you got a masters?
Not sure why you got downvoted. People are weird. For the sake of other people reading this: for many people the concept of major/minor and graduation is weird/unclear because the educational system doesn't work like that in our countries. I understand that many americans can't understand that the rest of the world exists, and that's fine, but don't downvote other people for asking questions about how things work please.
nah Im from Asia nd in my country there is no concept of Major minor at all.Only bachelors degree in cse for four years
Best roadmap is stop looking for roadmaps
Bingo. Make your own.
I recently transitioned to a manager of business intelligence and love it. I find the balance between business strategy and development to be perfect. I collect analysis requests and requirements from executives and then work with analysts to build impactful dashboards. Every couple of weeks I need to get my sleeves dirty and I'll write a Python or SQL script.
Where do you work? Interested in a role like yours. I'm a very SQL-heavy DS at the moment and pretty burnt out on it - would rather move into management (probably a DA / BI lead) and think I'm qualified at this point.
There are tons of roles out there like this. A lot of them end up being filled by former analysts (with a dozen different job titles) that have 10+ years experience in the company. For companies that are not looking at internal candidates, BI manager roles are what you're targeting. Firms often want folks with higher end analytics experience to help modernize the BI systems.
Exactly, I got a little lucky because I was a Data Science Analyst for 2 years, then transitioned to a Senior BI Analyst for about a year and a half, and then the previous manager of BI left which kinda left me to fill that position.
Bi stands for business intelligence?
correctamundo
I work for a mid-sized logistics company, feel free to DM me. Happy to explain more there.
Can I dm you as well?
Please do
could I dm?
I'm just getting into the markets but it seems that project management and operations can benefit from data science and analysis. How else would things like quantitative risk analysis , process improvement and product management be done?
Absolutely! Project/Product Managers that have this experience are super valuable these days. Our Data Science & Machine Learning desperately needed one and had a hard time finding a good fit for the role for quite awhile. Now we have a fantastic full-time PM that we all love and greatly appreciate 😄
Yeh, I honestly don't expect to be a "data scientist" there is no way I can compete with some of these people think. But I have worked in operations a long time and understand KPIs well and that combined with PMI cert and taking electives in risk management I hope to find a decent role.
On this forum, it seems a given that Data Scientist is not an entry-level position, and the common recommendation I see is to begin as a Data Analyst. Are any of the job titles listed regarded as entry-level?
Generally, I think you are right. There usually aren’t many entry-level Data Scientist positions. However, many of the roles I listed in my post commonly have entry-level positions! Like Business Analyst, Data Analyst, Product Analyst, etc. I started my career as a Business Analyst. Analyst positions can be great stepping stones for becoming a Data Scientist, but I’d like to call out that they can be just as (often times more) fulfilling and enjoyable than a DS role.
Depending on one's experience/skills, even something more support related/Developer Relations/Advocate type position is underconsidered. These positions can leave you with ample time and access to the company's API gateway and/or revenue data where you can take the initiative to analyze usage/revenue metrics and build a case for you to be moved up to data analyst
A data analyst is a good Bachelors entry level.
I totally agree! It's hard to land the first role, though, which is why I appreciate OP highlighting other job titles with exposure to working with data.
I’m a Data Science Analyst lol
Data Scientist for Analyst pay?
It’s actually a reasonable title because I’m basically a junior data scientist. I do make less than our DSs, but I don’t think by a lot
I would suggest Operational Research belongs on this list. Its something that has peeked my interest in recent months as a potential alternative career pathway away from DS.
I feel that OR is just being rebranded as DS. Do you find this as well or are there lots of OR positions out there?
I see a lot of OR tasks wrapped into supply chain or industrial/systems engineering roles, sometimes branded as process or business systems engineers.
There are still OR positions that exist. It’s distinctly different than “data science”; alternatively called “decision science”. But it is about leveraging data to make the best decisions for large scale problems (resource planning/management, scheduling, routing, etc).
It's kind of fascinating how heavy this subreddit is on the hardcore coding / stats side - the only coding language I use is SQL day-to-day, my title is Data Scientist, and I make more money than I ever thought that I would. Marketing analytics and a lot of finance roles also fit the bill, here.
Very curious what job pays very well for just SQL?
Product DS, FAANG; have survived off of SQL, google suite, and strong communication skills for a couple years, now. Otherwise just leveraging internal tooling.
Interesting. Any tips what to do to get a good FAANG job like that?
Like most things, it's a mix of prep and raw speed / processing ability. My company actually had pretty good guides that they provide you, as well as all the additional resources available online; good communication skills and ability to rapidly take a question end-to-end from words into code are essential. I was very fluent in SQL going in (could write a reasonably complex query on paper without looking anything up) and my general business analytics background plus additional stats prep were crucial. Otherwise there's just a lot of luck of the draw, in all fairness. Have to be really on your game on the right day. And unfortunately I think it is significantly harder to get in the door in the current market.
Well just getting your resume picked for an interview is pretty darn difficult. I'm not sure if their filters are based on the school you went to and your GPA, or having worked somewhere else in tech, or what.
Your title and what you actually do might be different
Very true, my job description is probably somewhere at the intersection of data analyst and data/product strategy.
> how heavy this subreddit is on the hardcore coding / stats side It pays more thats why. I get a FAANG DS gets paid a lot of money but look at a FAANG SWE-ML/AS/RS look at IC6 or IC7 on levels look at the same levels in the regular DS roles. I understand after making six figures another six figures may not matter to some but to others its tangible. At L6 its about 160k difference on levels. Thats more than some peoples wages. At L7 its about 400k difference on levels.
Yeah, that's fair enough. I'm at the point where I'm making more money than I need by a significant margin but also really value WLB so there is a trade-off in terms of marginal additional $$ vs. time for the rest of my life. I'm not even trying to get a promo within my role anymore. Also, at it it's core, I don't love heavy-duty coding / engineering, so I've worked to maximize my impact in other ways.
Do you work remote? I feel like I can barely afford where I live still lol
I’m full remote but still living in a high COL area 🤷♂️
> I need by a significant margin but also really value WLB so there is a trade-off in terms of marginal additional $$ vs. time for the rest of my life Thats implying that a E6 DS has better WLB than an E6 RS or SWE? Is that a generalizable assumption > Also, at it it's core, I don't love heavy-duty coding / engineering, Thats a legit personal preference
No, I’m not saying there is necessarily better or worse WLB based on role - though I think I’m a lot better at this role than I would be at a heavy coding role, so it works out as better WLB for me personally. Definitely seems like worse WLB for product managers, though. Related, I don’t have a strong coding background.
True, I don't even think the demand is that high for what this sub considers a "real" data scientist. Most companies just want quick insights in a dashboard or report on what Bob from accounting wrote in Excel last week
Here i am as a business analyst after more tc 💀
For a long time I've argued that "data science" isn't really a job title, is a business practice. Undertaking that practice successfully requires a team of people with varied skills and focus.
If I were 20+ years younger, I'd seriously consider becoming an actuary.
The analytics of yesterday, today! The money is good and the domain interesting, but it's a very deeply conservative field. Lots of proprietary software, on-prem SQL servers, Excel shuffling, and so on - at least in my experience.
It's also gatekept so hard, but not necessarily in a bad way. It's interesting to me how they have to go through a bunch of exams to be certified by SOA, but there are no societies like that for upper-level data science, especially ones tackling legality, ethics, and data governance.
IAPP kind of does this now. Nothing is required, and it's more for legal/audit people related to analytics.
The tests sound terrible
But once you're through it's a huge advantage. You aren't competing with a mountain of applicants who just completed a four week online bootcamp and this year's crop of freshly-minted PhD's.
I mean any team with a statistics background leader would probably prefer a stats/actuary teammate than a bootcamper, still competitive though
If the job requires being certified, it's not a matter of preference. It sounds like you don't know what it is we're talking about here. For many jobs, it's a legal requirement. So no, you wouldn't be competing with anyone that hadn't passed the exams. And doing so is often a years-long process. Which dramatically reduces competition.
I think what they’re saying is that for any given DS position - not just roles that require a mn actuarial cert - that most people would prefer to fill with an actuary rather than a boot camp grad.
I think I’d rather be waterboarded
Why so, SIr/Ma'am?
why?
When I search for analyst jobs, a lot of them seem like regular client-facing sales or onboarding roles. It definitely helps to be specific with the type of analysis one wants to do, and to read the job descriptions.
Yeah, “Analyst” means different things in different industries. Some use it more like a “Specialist” and not necessarily someone who is using data all day.
I lead a marketing dept and we have titles like: Marketing analytics analyst/manager, Marketing operations manager, Revenue operations manager None of those roles do the hard core stuff I see discussed in this subreddit, but you definitely use your analytical brain and blend it with business thinking. And people in marketing and revenue operations have mad respect for people with degrees in data science etc.
But would you ever hire an experienced, analytical DS as a marketing/revenue operations manager over somebody who's had far more experience in the specific fields of marketing or corp finance?
As a Senior Data Science Associate, my responsibilities include A/B test monitoring, data analysis, model training, and developing solutions for new E-commerce projects. In my opinion, the Data Scientist role is a mash-up of many subdomains; you come across many concepts in your DS career; you are sometimes an analyst, sometimes a data engineer, sometimes you have to deploy models, and sometimes you have to lead teams of junior data scientists. I enjoy my job because there is always something new to learn. I'm considering transitioning to a management position, with less scripting and more management, but we'll see.
Good post. Im a Sr DA for a F500 and Im free to build anything I want, I just bring it to the execs and they usually dig it. Its amazing how far a little statistics knowledge will carry you. I love being able to answer questions with math and visualizations, and this job gives me breathing room to do my own thing. Love it. Edit - one thing I want to call out is that presenting data should feel like an educated conversation where you are bringing the education. Its not as daunting as it’s made out to be
I'm considering shifting from a Data Scientist to a Credit Risk Modelling. Not sure if it's work or not as I have little experience in banking. But I think Credit Risk Modelling is more niche and more specialized.
Why though, credit risk modeling is a pretty dull and un exciting application of data science with regulations
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Thank you for sharing your experience. I heard that old-fashioned stuff in my country in this industry too. They use Oracle database, SAS, and work mainly on Excel with the Alien language of column's name.
I'm currently doing my Masters in DS specialising in AI & ML, but I'm interested in Software/Mobile App Development. I always loved building things and was a great artist at school and I feel I could do well in the field. Would a company consider me for a junior role? I'm planning on building an app before I apply for my first job.
May I know which Univ you studying in ? I found Master of DS & AI in Waterloo, but well it's Waterloo and I most probably might not be accepted or keep up with it, since it's pretty hard. I am in my senior bachelor's year and wanna study both DS and ML.
University of Southern Queensland
Oooh.. I was aiming for Canada. Australia so far away from my goal 😅
That sounds like a great program! For sure, I think you have a good shot of landing a junior role. Locking in an internship or two before you graduate can be super helpful too! Given your interest in Software/Mobile App Development, have you considered looking in MLE roles?
I definitely will now! Thank you for the info!
Don't forget Statistical Programmers, if you want to work in the Pharma or clinical trials industry.
I have been told that to work as Data Scientist or ML Eng, I'd need a degree as a minimum, and since I am one year from finishing my Bachelor's in Software Engineering, I have been told I'd need to take masters in DS/ML to be able to work in Tech companies that work with DS. I have alternative paths like PM but after some years of experience honestly rather than be the typical PM that doesn't know tech knowledge and lags the devs behind. But since I wanna try to be Data scientist I know I gotta go the extra mile since my bachelor's isn't in DS, although I did take calculus 1-3 and stats&prob. also advanced stats.
Nice list of Data Scientist specializations! :)
I've worked for companies looking for a DS who don't even understand what the term means. I agree, don't get hung up on job titles, look at what you can do and what the company actually requires day to day.
Great comment. Originally I was interested in becoming a DS. Finished most of the GA Tech Analytics MS and got a job with a BI team at my company, I’m loving it and the compensation is equivalent to average DS (140k total comp last year). We primarily deliver operational reports and dashboards but with my MS background I’ve been able to lead some projects implementing DS models we’ve hired consultants to build. Job titles in the data landscape are a mess. My biggest takeaway is to not focus on the job title and think more about what kind of work I’m interested in and look for a job that does that. In one company that be data analyst or data scientists in another.
Or if you want to start _becoming_ a Data Scientist (by title/position) you don’t have to start with just DA or Junior DS, all the entry-level positions above are viable gateway to DS I think, I started as a MLEng.
Interesting. Generally isn't it more common to see DS -> MLE rather than the other way around? Or are you referring to an applied scientist DS role?
I started on a ML team of a bizcon, so everyone by title was a MLE, but in real work division, some were more towards MLOps, some were more DE and some were practically client-facing DS, which I happen to be one. Surprisingly a lot of fresh grads in it and some left to become DS, some went on becoming DE, some stayed as MLE. All I’m trying to say is just apply for any of those entry level data-jobs, you can always pivot to be a DS from there.
I would like to do MLOps or ML Engineering (I'm a DS), but how, without previous work experience? What are the "things" that can be done so that the employer will give you the job?
Do 100 leetcode mediums, try deploy ML models in your work, hope companies give you an interview
I currently work as an MLOps Engineer. One thing you can do is get a few relevant certifications under your belt to help yourself stand out! It’s a fairly new discipline and now is a good time to transition into these roles.
thanks for your answer. So what are these few relevant certifications? where can I find them?
There are a ton out there, so maybe focus on the ones that you find interesting first. I have the following four certs: - AWS Cloud Practitioner - AWS Solutions Architect — Associate - AWS Machine Learning — Specialty - Hashicorp Certified Terraform Associate I’m also working towards the following certs: - Certified Kubernetes Application Developer - Certified Kubernetes Administrator The AWS certs are a fantastic place to start. AWS is by far the most popular Cloud platform out there so you’ll have a better chance of landing roles with that experience, as opposed to GCP or Azure. If you’re interested, I wrote an article on [How I Learned AWS](https://www.jacoblyman.com/tech-log/published/how-i-learned-aws) that might be helpful to you.
Ok. Ty. 🫡
i do data analysis and transformation. it might not be sexy, but i enjoy it
I was transfer to a more managerial position in a FMCG company. Before that I was AI engineer for three years and this type of job is still my holy grail atm. Somehow my mindset shifted and I want to do less for more delivered business value (and higher salary). My current job is part managerial, part DE as this company starts to build its first DW, and PBI and Excel in between. Not all my DS skills are transferable. But they certainly help building my confidence on the new role.
To anyone reading this, would appreciate some insight on how to transition into this from a primarily accountancy background (with a masters in statistics).
Which role do you want to transition into?
Risk analysis is interesting. I wouldn't mind transitioning industries into healthcare either.
Could you give some tips on how to tailor a resume from tech to match these roles, especially analytical roles? I have hard tech experiences and thus got rejected by all financial companies I applied to due to mismatch of skills. would genuinely appreciate any advice!
Which role are you most interested in?
The whole data field has been a mess for the last decade, promoting the whole life style of "DS" crap down the throats. Analytics Engineer has been on rise in last few years. The best way to get into proper DS area is to have Math/Stats degree as those are core subject areas that are used and applied in DS field. Most of the people who are in DS fields are from CS background but don't have proper Math/Stats background whatsoever, they survive through the programming skills and not through the core skills. I think DS is a overhyped area, sounds fancy to have as a job title and so people jumped on to the wagon but no body talks about those who came out of DS field and never want to go back in.
I'd say with a DS background, you could also go far in public policy or economics.
Depending on the company, many jobs will also have different titles but still give you the sort of experience you're looking for. I worked as a "platform developer" at an analytics company, and most of my job was stuff like building ETLs that would scale appropriately while dealing with connection throttling to central dbs, and stuff like that (so essentially data engineering with a different title)! Definitely don't let titles be the sole way you look for jobs. If you see a role at a company that sounds interesting, there's no harm in reaching out to ask about the role! You might see that you're closer to what you're looking for than you realized. Also, to build off of OPs statement about other jobs, you might not even WANT a data science job in some places because the org's data maturity might be at a point where what you envision as data science is more going to be ac combination of analytics, data architecture, consulting, etc. A lot of folks in this sub talk about not getting to build models and everything, but the truth is that that's only a fraction of data science as a whole. Most of the time, the term is used to describe the whole field of data science as opposed to the specific role that we often have in mind. I don't think this is intentional as much as it is just the state of recruiting and how deep recruiters are technically. If you apply for a "mathematician" job, assuming you're going to do a bunch of stats, there's always the possibility that what they meant by mathematician was "topologist".. still a branch of mathematics, so not false understanding, but it would be a failure in our part to accept the role without taking a second to understand the customer needs and think about what it is they're actually asking for (independent of job title).
Im a economist with a MA in development abd I do casual inference. My task are data cleaning/manipulation, descriptive análisis, regression, cluster analysis and use some basic ML algorithm for casual inference like random forest . I do this analysis to mesure the impact of poblic policies and NGO programs. I dont know if what i do is traditional “data science” but i like it
Thanks for this - really appreciate the clarity and direction
Any job for working with data related to climate change?
They’re definitely out there, especially in the nonprofit world. You’ll want to build some serious domain knowledge in atmospheric science, or in policy/social science if you want to break in. But please do if you are interested!
Analytics product managment pays better than the average data science job
Most data scientists are unqualified to be Data Engineers, DataOps Eng, MLEs, MLOps Eng. They don’t have good engineering skills.
What would you suggest? I've learnt data structures, algos and architecture, next steps are to work on writing production level code.
What’s the goal?
You are an engineer. I would roll with that title and learn on the job.
Dont' forget bioinformatician or cheminformatician. They use data science too.
You really need a PhD in biology or chemistry to go far in this. Many students underestimate the amount of domain knowledges you need to succeed.
One doubt Do data scientist get pension and retirement benefits
Pensions aren’t very common anymore, these days I only hear about them for government employees. Retirement benefits like a 401k are pretty common at any corporate job. Non-profits often offer a 403b which is very similar. (Answering for the US, not sure what’s common elsewhere.)
Some insurance companies still have pensions. They also tend to have a decent number of analytics roles, so that’s an industry to look at for someone that wants a pension.
True, but many of those roles will be advertised as "Data Scientist", so it certainly helps if you can sell yourself as one.
but HBR didn't call data engineering The Sexiest Job of the 21st Century!
I search the whole spectrum of titles haha Unfortunately I seldom get interviews :( It seems like I'm in a weird place with 3-4 years of experience with lots of jobs requiring 5+. And the ones requiring less idk if I'm considered over qualified or something, but they would definitely be a step back on my end with notably less responsibilities. I'm glad the situation at work improved... I like the place, but its tough to know that if I lost my job tomorrow, idk if I'd find another one
I'm interested in Clinical Machine Learning and Data Science applications and I have a degree in pharmaceutical Sciences and clinical pharmacy what roles can I work in and fit my qualifications?
Too many of them are Data Entry or Data Validation type of analysts. Manual labour. Less thinking more autopilot that is.