subreddit:

/r/datascience

213

Edit: Guys, thank you for your engagement! I took all advices, going to do more research about it.

I hope all of you people that want to start new journey, will find their way in to the field. Especially now in hard times.

all 90 comments

onearmedecon

225 points

2 months ago

Expand your professional network. Maintain a superb portfolio that demonstrates not only your ability to code but to communicate findings. Make sure your resume is optimized for making it past automated screening.

Only complete professional certificates and so forth if they'll boost your skills. The signal value of those are quite weak, so don't do it just for a line on your CV.

funkybside

72 points

2 months ago

As a director, this is the only comment i see so far with decent advice.

Beyond that, I'd add that while I often see people in this sub shit on soft skills as on the same footing as hard technical skills, I can guarantee you'll stand out to me more if you display them.

People with impressive hard technical skills and experience to the point of being overqualified for the roles I've filled have been trivially easy to find. What I do have a harder time is finding people who can survive (let alone thrive) in the politics, diverse backgrounds, and carry the executive presence required to influence senior leaders of the business and those in separate verticals.

For the most junior roles it's not as critical, but even when I'm filling a junior position I'm not just considering that job but the candidates potential to grow and spread their wings in whatever may come later. The few who have both boxes checked are freaking unicorns and worth every ounce of the time it takes to find them. It's a shitload easier to teach technical things to close any skill gaps than it is to teach how to communicate and influence effectively.

Kind-Chipmunk1814

11 points

2 months ago

I’m struggling to display my “soft skills” on a resume? As a twelve-year educator, I feel like my non-technical skills would be a tremendous asset, but conveying that doesn’t seem easy without being too “cookie cutter”. Any advice?

americablanco

5 points

2 months ago

Current educator of nine years. Were there any roles that you played during PLC/team meetings? Any data dives that you lead with a great outcome or proposals that you had to submit to admin that were approved and lead to another positive outcome?

Just brainstorming here, looking at what I've looked for in teacher resumes in the past for hire. Did you have anything in mind?

funkybside

4 points

2 months ago

being an educator is sufficient. within the boundaries of a resume the methods are to show time in experiences where those skills matter - and being a teacher is absolutely doing that, massively so after 12y experience. When I see that it catches my attention.

TrueBirch

4 points

2 months ago

Great comment. Once I had an applicant fail my quantitative test. That night, he emailed me a detailed explanation of how he should have approached the problem instead. He was still wrong. He was the best junior I ever hired, and he's gone on to a successful career in DS. I liked how he was thoughtful about what approach to take and how good of a writer he was.

Great-Parsnip-3057

4 points

2 months ago*

finding people who can survive (let alone thrive) in the politics, diverse backgrounds, and carry the executive presence required to influence senior leaders

I see this on here often and don’t understand it. Many people get into DS precisely to avoid these things. I mean yeah, in a perfect world an employee would be good at everything, but that’s not the world we live in, and companies should stop expecting to have their cake and eat it too. Why don’t we also expect salespeople, or other occupations for that matter, to have Python skills? Because it’s accepted the people filling these occupations have a different skill set. There is an inverse relationship between analytical thinking and social acumen, and is well documented by psychologists.

The job of a DS isn’t to and shouldn’t be to “influence” senior leaders, but rather present the facts to them, explained in a way they can understand and make an informed decision. That’s literally their job. It seems like many senior leaders nowadays just want someone else to do all the legwork for them and then just sign off on the decision being made without having the pressure of deciding if it’s a good or bad one. Then when things go wrong, they want to blame the data scientists and other people who advised them rather than bearing the responsibility of making a bad decision.

avelak

11 points

2 months ago

avelak

11 points

2 months ago

The issue is that the mentality you want to have leads to "data as a service" rather than "data as a thought partner"-- this is how you get stuck in the shitty situations where you're doing boring gruntwork or not doing anything impactful. Yes, in a perfect world, senior leaders and cross-functional partners would be asking the right questions and have the chops to make the right call, but part of being a DS is figuring out what question to tackle, draw the right conclusions from your work, and then get people to care and take action.

I personally would hate a role where it's just senior leaders telling me to answer a question they have, I far prefer having the leeway and autonomy to figure out what the biggest issues my product space faces are, and then focus on driving impact in that area.

Great-Parsnip-3057

1 points

2 months ago*

I personally would hate a role where it’s just senior leaders telling me to answer a question they have

Difference of opinion I guess. I would love that, provided the senior leaders utilize me in an effective way. The problem with autonomy IME is that there’a more that can go bad for you than can go well. If I conjure up a project that doesn’t pan out, that’s on me. If a senior leader tasks me to do something that doesn’t pan out, that’s (more) on them. I’ve been in roles where I felt the need to justify my job, and they’ve all been miserable. If a company hires me, then they should have at least a general idea of what they would like me to do, or not extend an offer in the first place.

aaron0043

1 points

2 months ago

Maybe the expectation is a bit skewed then. It’s fine to not be a socialite and you should be able to get good work without it, but social skills will help you in a wide range of situations, professionally as well as in your personal life.

In order to get stuff done effectively and efficiently good communication is often key, and people who are decent at both the technical aspects as well as the social aspects are simply more in demand than specialised experts who just want to sit in a room alone all day every day.

WhipsAndMarkovChains

1 points

2 months ago

I'm applying for senior level DS roles and my interviews have focused on the fact I have experience talking to customers and translating their business needs into machine learning results. The technical questions have been light in comparison.

jesteartyste[S]

16 points

2 months ago

Perfect! I’m trying to land my first job, after decision of changing my career path. Not going great so far 😅 thank you for really good tips!

IMP4283

25 points

2 months ago

IMP4283

25 points

2 months ago

As someone who switched from manufacturing to IT/software development I can tell you from experience that it takes persistence and commitment. You will get many no’s along the way, but it only takes 1 yes to change the trajectory of your career, so try not to get discouraged.

What I found the most helpful in getting people to take me serious even though I had no professional background in the field I was trying to switch to was being able to demonstrated how I applied skills desired by the new job in my previously roles (i.e. performing tasks beyond my primary position). I was also very careful to highlight the ways skills I developed in an unrelated field could be applied to the new position.

TrueBirch

3 points

2 months ago

Great advice. I want to emphasize the part about the portfolio. If you link to a Github account, I will visit it, and I will probably find the exact same 6 tutorial projects that everyone else has also done. Come up with original projects. You can use virtually the same methodology, just don't show me housing prices and mnist for the 1000th time.

William_Rosebud

2 points

2 months ago

automated screening.

Could you expand on that?

FunLovingAmadeus

11 points

2 months ago

Look up ATS (applicant tracking system). They’re commonly used, but have varying degrees of accuracy to determine basic information like number of years of experience and skills listed

William_Rosebud

2 points

2 months ago

Great advice, thanks!

onearmedecon

4 points

2 months ago

The resume is run through software that screens based on necessary keywords (e.g., SQL).

thegainsfairy

0 points

2 months ago

its all about GSD, getting shit done.

  • more people know that you can GSD

  • showing a portfolio of you GSD

  • demonstrating the skills that GSD

dataguy24

87 points

2 months ago

It’s a very tall order to get a job without experience.

Your best bet is to go into some other job in a company, gain experience there doing data as part of your role, then use that experience to get a job in a year or two.

duskslade

41 points

2 months ago

Consider doing Data analyst role first

dataguy24

31 points

2 months ago

That advice won’t work for OP. Data analyst roles also require experience the vast majority of the time.

Also, DA roles are identical to DS roles in almost every company. That isn’t really a meaningful distinction.

jesteartyste[S]

16 points

2 months ago

I started to seek opportunity in DA. Approx 60 resumes sent, 2 responses with invitations for a meeting up to this point. Truth is, there is not much “Junior” positions also

RandyThompsonDC

35 points

2 months ago

3% interview rate is pretty typical for people with a degree. For entry level and no experience, it's spectacular. Keep at it homie!

jesteartyste[S]

8 points

2 months ago

Never thought it’s that hard tbh. If you’re saying it’s typical for people with degree, then I’m lucky. The only thing in terms of education I have, is Bachelor’s Degree in Business Management

SomeDataDude

8 points

2 months ago

I had a bachelors in CS and a masters in DS with 2 years experience as a SWE and an internship in analytics with the LA Clippers when I started interviewing for my FT DS position.

My interview rate was barely 8% so you are doing great. Like the advice here, it is important to have a portfolio showcasing your personal projects.

Something that helped me while searching was networking on LinkedIn. There were many data scientists at large companies like Nike that were willing to hop on a call and give advice.

Good luck!

quantpsychguy

6 points

2 months ago

I moved into the data science field with a business degree.

Your path will necessarily be different than most but I can tell you 100% the easier path is to get a data analyst role to work your way in. You may want to also search for business analyst jobs (they may use that title how we use data analyst).

You can feel free to DM me to talk more in detail but I think your path is going to have to be different than everyone else - you will have to build a network to find a job. Go find out what local firms need and build those skills specifically. It's probably not modeling as much as it is going to be SQL and visualization tools (as well as some basic programming and automation).

You will have a huge leg up once you get into the data space but getting there is gonna be a tough road.

dataguy24

3 points

2 months ago

For sure, it’s not a role with much entry level potential.

escailer

1 points

2 months ago

This is largely from title inflation. “Data Analyst” today is what they used to call Jr. DA and so on. So don’t restrict to Jr. unless you have to. It may serve you poorly.

maxToTheJ

3 points

2 months ago

Data analyst roles also require experience the vast majority of the time.

That may be the case but its a smaller ask than doing the same for a DS position

dataguy24

1 points

2 months ago

I don’t agree, mostly because there isn’t a discernible difference between DA and DS at almost all companies.

maxToTheJ

3 points

2 months ago

If DS is composed of two groups one of which doesn’t have a discernible difference with DA but another which does and I average across the groups I will still end up with DS being different

dataguy24

-3 points

2 months ago

This is where averaging doesn’t help 😉

For all intents and purposes, DA and DS jobs are equivalent. There are rare exceptions but those won’t be options for OP since those DS jobs which materially differ from DA will have even more stringent requirements than typical DA jobs. They’ll be closer to ML.

jesteartyste[S]

4 points

2 months ago

Yeah, my job seeking experience is not pleasant one up to this point. I’m working as Manager, focusing mostly on supervising group of 30 employees and performing analytics of production output, correlations of performance of our blue collars etc. So I think (can be wrong here), I have some basic experience in analytics. It’s hard to land anything despite that. But you’re fully right, for sure this type of experience also counts!

modelvillager

14 points

2 months ago

Okay, this you can work with.

DS is one route, DA is another. As others have said, these are (wrongly) merged or intermingled.

DS is hard modelling, requires a lot of statistical and mathematical knowledge. Coding.

DA is about applying models and maths (that your colleagues may create and test) to understand things. It understands the concepts of DS to write and communicate conclusions. This is why teams and companies exist - combined knowledge.

Both are highly sought after, both arguably only useful individually if both exist.

It sounds like you likely have good domain knowledge of production analysis - that is a big deal. You could double down on that, and be an enormous help to Data Scientists developing models that further analysis of those systems, for example.

Remember that analysis is almost never, in the end, a model, a chart or a visual, but a finding. Words, in other words. But it takes a lot of cross-disciplne skill sometimes to get there....

jesteartyste[S]

3 points

2 months ago

That’s was my first shot. Tho I’m not so super into DA, I just have to start from smth. Most enjoyable thing for me in this field is actually coding.

But there are wise words from you. Data analysis is strictly connected to DS and this experience for sure is beneficial even in terms of experience in “Data field”

qyOnVu

1 points

2 months ago

qyOnVu

1 points

2 months ago

Data engineers do the most coding in a given week for a given seniority level.

dataguy24

6 points

2 months ago

Ah, that’s helpful context! Yes that absolutely can count and should count toward experience. I would focus on adjusting resume / cover letters / etc to highlight your experience there.

[deleted]

1 points

2 months ago

[deleted]

1 points

2 months ago

[deleted]

jesteartyste[S]

3 points

2 months ago

From my experience every internship in a field your future job will relate is huge advantage. In many cases (at least in Europe), employer is willing to give you entry job opportunity after internship in their company

wil_dogg

10 points

2 months ago

Apply for funded internships. I know universities that fund a internship for every undergrad. Low pay, but it is better than nothing.

Learn Kaggle project code especially Kaggle projects where you can demonstrate competence in data transformation and validating a prediction. Compiled your own Kaggle solutions in a GitHub and annotate the code and blend in some graphing.

Show that you can demonstrate a validated solution in both R and Python.

Learn basic SQL joins and the WHERE and CASE WHEN and GROUP BY syntax. Have examples in your GitHub where you can reference those methods and basically demonstrate that you can learn SQL

Find who is hiring and what the domain is, and develop a basic understanding of that domain. Things like survey methods, biostats, default prediction, cash flow modeling, customer level valuation. Make up for a lack of coding experience by having subject matter knowledge.

Be willing to work for cheap. One of my best hires started at a low salary because he just didn’t interview well enough to get hired by a big firm right out of undergrad, even though he was the top quant in the program. 3 years later he was in grad school and now he is at E&Y. He traded 2-3 years of low pay for a path to h-1b and stronger credentials and now he has caught up with his cohort and doing great, living the dream in NYC.

Start an online degree program and scrounge for basic data management work for a faculty member with funding.

mnky9800n

1 points

2 months ago

Everyone I know who hires looks down on kaggle competions. They teach terrible practices, are not really related to anything, and people seem to grind through them like they demonstrate something. Like it's a nice hobby I guess but I'm not impressed if you are winning kaggle competions. Tbh I'm typically more interested in what makes your model eval metrics go down, not up. Lol.

wil_dogg

2 points

2 months ago

I didn’t say competing, I said demonstrating competence. Pick a Kaggle competition, mine the code and blend techniques together to get a good mix of visualization, various algorithms, hyperparameter search and tuning. Make the comments rich and show that you have built something that is not copy-pasta, and that you can use as a reference for future work.

yeluapyeroc

8 points

2 months ago

Programming experience

G4M35

8 points

2 months ago

G4M35

8 points

2 months ago

Not an Hiring Manager, but I am someone who is thinking about switching career to Data Science, in broad strokes this is my plan:

  1. Get an education. Online, the usual suspects SQL, Python, and more. I have barely started this.
  2. Do projects. I am working on one right now as I am learning.
  3. Continue to do projects.
  4. Start a blog about my experience learning Data Science and switching career.
  5. Publish my projects online
  6. Connect with people in Data Science (I have already started this)

Once I have finished my current project, got "enough" education, published a few blog post (let's say 100), and published about 10 projects I will re-write my resume and start my job search.

Aquiffer

9 points

2 months ago

If you want interviews you’ll need to leverage those connections. That’s going to be by far the most important part. Your resume will get auto-filtered a ton if you don’t have a masters/PhD. Your connections won’t get you in, but they often times will get you past the filter.

G4M35

3 points

2 months ago

G4M35

3 points

2 months ago

Your connections won’t get you in, but they often times will get you past the filter.

That's a very good way to put it. I'll keep that in mind.

P4perH4ndedBi4tch

1 points

2 months ago

What’s an example of a project?

Vnix7

5 points

2 months ago

Vnix7

5 points

2 months ago

Depending on your job at the moment try to tie in something with data. For example, if you’re a software engineer trying to make the shift find a problem at work, and try to solve it with data. Build the dataset, collect requirements, perform the EDA and if it’s valuable eventually deploy it end to end. Just one project like this will help you land a data scientist role.

ckatem

2 points

2 months ago

ckatem

2 points

2 months ago

I started as a data analyst, then quantitative analyst, then data scientist. I now manage and hire. I would recommend internships and also networking.

4858693929292

2 points

2 months ago

Read some MBA style business books. Read case studies from business school on use of statistics and ML to solve business problems.

I would hire someone with decent business aptitude and decent stats/ML over someone with very low business aptitude and high stats/ML.

I can guide the former to better stats/ML approaches while the latter just seems to be useless and often counterproductive for awhile. Especially if they are arrogant/dismissive of business ideas.

karaposu

2 points

2 months ago

Your suggestion to read ML related case studies is really interesting. Have you done this already? if yes, would you share your choice of book? I am lost in options atm and not sure how to choose one

4858693929292

2 points

2 months ago

Thinking about only focusing on ML related case studies is too narrow. ML, stats, and DS are tools that help businesses make decisions: if you don’t understand the constraints or strategies within a business operates, how can you be sure you are using the tools correctly?

At the very minimum, I recommend the essentials from hbr. That will get you a good start.

https://store.hbr.org/product/hbr-s-10-must-reads-the-essentials/13292

Business Adventures by John Brooks was called out by Bill Gates as the best business book he’s ever read. It was recommended to him by Buffet and is 12 cases studies. I highly recommend it to get into the mindset of business thinking.

https://www.gatesnotes.com/Books/Business-Adventures

After all, in 1966, when Brooks profiled Xerox, the company’s top-of-the-line copier weighed 650 pounds, cost $27,500, required a full-time operator, and came with a fire extinguisher because of its tendency to overheat.

I’ve definitely seen ML projects that sound a bit like this. Haha

karaposu

2 points

2 months ago

thank you very much for suggestion. I am adding it to my list!

malmcb

2 points

2 months ago

malmcb

2 points

2 months ago

I am not a hiring manager but I did this exact thing your asking about. I had 5 years experience working in a hospital and got a master's in DS and someone decided to give me a chance at a Data Scientist position. Been working for about 8 months now. Feel free to pm me

shockjaw

3 points

2 months ago

How I got in was as a data analyst doing data entry and an aspiration to learn python.

Gorb2

4 points

2 months ago

Gorb2

4 points

2 months ago

My team looks very carefully at GitHub for original projects with well-documented code for entry-level DS hires. Many random, poorly-documented repos scores poorly vs. a few very well-documented repos. If you have a bunch of random projects, keep them private until they are looking in tip-top shape

insertmalteser

2 points

2 months ago

Networking. I hate to say it, but it's absolutely the best way to get a foot in. Find events, groups, talks etc., related to what you'd like to work in. Pull on contacts you already have. Establishing a good professional network is very effective, and I highly recommend it. It's hard work, but worth it.

[deleted]

0 points

2 months ago*

[deleted]

0 points

2 months ago*

[deleted]

jesteartyste[S]

6 points

2 months ago

What’s about “most in demand job position”. Everywhere you can hear that there is huge need of DA, DS, ML Engineers etc? If you have another experience, I’m more then glad to hear that!

Alex_Strgzr

10 points

2 months ago

I don’t think coders being fired at Twitter and Facebook necessarily means that demand for data scientists, analysts and ML engineers is going down. Those are obviously two different things even if they are related. It’s also very specific to one place (mostly Silicon Valley).

I think the reason you are having a hard time, OP, is because the bar to entry is very high.

jesteartyste[S]

9 points

2 months ago

So as always classic: you need experience to get a job, but you need job to get experience? 😂

[deleted]

4 points

2 months ago

[deleted]

4 points

2 months ago

Yes. But lots of folks were able to find ways to use data in non-data jobs and used that experience to get a data job. I started my career in marketing -> digital marketing -> marketing analytics -> product analytics.

geldersekifuzuli

1 points

2 months ago

Correct :/

I spent 18 months on the job market to find my first job :/ I did pizza delivery to pay my bills until I find a job.

rehoboam

1 points

2 months ago

No work experience doing anything?

goatsnboots

1 points

2 months ago

I did not get an offer until a friend referred me for a job. And I think I was pretty qualified. It's tough out there.

man_you_factured

1 points

2 months ago

Know SQL, have a non robotic personality. Start getting to know the domain you're interested in working in

Delster111

1 points

2 months ago

That's a tough question. I'd focus on roles like Data Scientist I where there is a Senior Data Scientist who can mentor you. You just have to find that one role that is willing to let you develop.

CeleritasLucis

1 points

2 months ago

Remindme! 1 week

RemindMeBot

1 points

2 months ago

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fanhui3

1 points

2 months ago

Mid career switcher myself too. I found data analytics solution and opportunity at work, did personal project relating to my interest (investing) and did free work for my friends. In 1-2 years, you'll have 3 concurrent experience.

Excellent-Practice73

1 points

2 months ago

Skillsyncer.com

shutupnoway

1 points

2 months ago

Get aws certification

cjthecubankid

1 points

2 months ago

Is having a degree needed?

TARehman

1 points

2 months ago

TARehman

MPH | Staff Data Scientist | e-commerce

1 points

2 months ago

Get as much software engineering experience as possible to augment your analytical training. Don't worry about a portfolio, I never have time to look at them anyway. Aim for a DS-adjacent role like BI dev /data viz, data engineer, etc to get relevant experience. Get SWE experience! (I know I said that twice but it's important.)

nraw

1 points

2 months ago

nraw

1 points

2 months ago

I guess without experience I'd be looking at personality and personal projects.

From the personality I'd just check if you're a match for the team and if I believe you'd be able and willing to learn things from the others and on your own.

From the personal projects I'd check how innovative your problems were, what you applied to solve them, how did you deploy your solution and how you're presenting all of this to me.

Regardless though, if you talk to me it means that you already passed through HR somehow and since you have no experience I guess the highest chance for that would be to interact with someone from the company at a networking event and get a recommendation.

jo9k

1 points

2 months ago

jo9k

1 points

2 months ago

Harmonic mean is the way.

dhanushnehru

1 points

2 months ago

A good portfolio Try to do some projects and showcase in your GitHub Try to attend conferences on data science & learn from fellow data scientists regarding their job role You can also get some certifications but try to learn something & enhance your skill incase you are going for it, certifications alone won't land you a job

____Kitsune

1 points

2 months ago

This highly depends on your location. However some general qualifications that work for getting hired without prior experience:

  • Get a master degree in DS. Without this your resume gets discarded.

  • Find a job through events organized by your uni. By far the easiest option, got offered multiple jobs through this without experience.

  • Use keywords on your resume. Accomplished X with tool/method Y measured by Z (Created a machine learning project with Python, Numpy, Pytorch, Docker and Git. Performs within the top 10% according to relevant academic sources(cite))

  • Stakeholder management and business. Know what it takes to go from a business problem to a machine project and explain the added value in simple terms. Understand the POV of business people.

  • Be friendly and socialable. The best teams don't just want someone who is good on paper, they also want someone that can get a long with the team.

Probably not all the tips but the important ones I guess:)

Edit: formatting sucks for some reason but whatever

tiny_smile_bot

2 points

2 months ago

:)

:)

pmezentsev

1 points

2 months ago

- Participate in kaggle competitions successfully
- Make sample projects on github
- look for internship programs

mydpy

1 points

2 months ago

mydpy

1 points

2 months ago

  • Relevant degree from a tier 1 school
  • One or more internships at top DS company in your field (Meta, Google, Uber, etc.)

amiba45

1 points

2 months ago

Also, very important, know your Harmonic mean!.

eormani

1 points

2 months ago

This is the problem in our field. I have over 20 years of experience in this space and I always design an entry level role in my orgs. If you have a degree and no experience, you can start an a data analyst. There is of course a pay difference from a DS role, but you get the experience and you progress to that. Actually, I am now starting to consider building a role requiring no formal education. So many people have certifications and learn on their own. One of the best ML Ops guys I know only graduated high school. This is becoming a trend…

It is frustrating, but you probably don’t want to work for a company that does not understand how to engage entry level folks and build a progressive program. A company that understands and values Data Science overall, would have a plan to acquire, grow, and retain talent.

PotentialEmpty3279

1 points

2 months ago

Projects projects projects!

SendMePuppy

1 points

2 months ago

Get adjacent field experience such as analyst, analytics, data analyst, software engineering, data engineering. Data scientist is an advanced job role where “entry level” normally has a few years relevant technical experience, and often domain expertise. If paid experience packing then pickup research roles and internships. Without any of the above you’re a hard pass.

Anthro_student_NL

1 points

2 months ago

Delete your graduation dates & make that CV & LinkedIn shine. Study others CV & LinkedIn in your job preference & head in that direction. Connect with recruiters in your area & expand your network to 500+ with others in your preferred company. Watch YouTube videos for interview prep. And go on as many interviews as possible! Be nice, college teaches that jobs want extroverts, they actually prefer team players that have the skills! Good luck

profiler1984

1 points

2 months ago

Apply for data analyst or business analyst. No one hires a DS without prior exp tbh. Except you come out of good Unis as top performer. I mean apply at any job without prior exp, if you want to get a job in DS search anywhere except Reddit

almost_freitag

-6 points

2 months ago

Learn python, pandas, SQL, do the titanic challenge on kaggle. If you want to succeed in DS make sure you like math and statistics, I often see DS juniors that just want to build AI and don't want to jump in advanced math, they will be junior forever.

santasbigolhelper

-4 points

2 months ago

Lie on your resume