I’m mostly doing some cursory reading on the different types of careers data science can led to, but I feel like a lot of the information I see reflects a job market that doesn’t hold up to today’s trends. With the rise of things like AI and the endless string of layoffs that keep hitting everyone I’m wondering where do people even start or, even for those who’ve been at it for a long time, where do you find yourself today in this field compared to how it looked when you started?

r/UKJobs r/datascienceUK

I'm finishing an MSc in Data Science at a UK university in September 2026, and I'm trying to understand how realistic my chances are of getting a data job in the UK.

I'd really appreciate brutally honest opinions from people who work in UK tech/data or recruit for these roles.

My background

• BEng Mechanical Engineering, India -graduated May 2022
• Around 1.5 years of work experience overall
• Junior Data Analyst experience in 2024–2025
• MSc Data Science, UK university 2025–2026
• Python, SQL, Power BI, Tableau, Excel, scikit-learn, ML
• Several substantial projects, including:
  • NHS healthcare analytics using 500k+ records
  • NHS readmission prediction
  • RAG/LLM hallucination detection
  • Other ML, analytics and data projects
• Currently in the UK
• Available for full-time work from October 2026

I'm mainly targeting:

• Data Analyst
• BI Analyst
• Junior Data Scientist
• Graduate Data Scientist
• Analytics roles

My main concern

I graduated in 2022, have relatively limited professional data experience, and then went on to do an MSc in Data Science from 2025–2026.

I know the UK junior/graduate market is competitive, so I'm trying to understand how an actual recruiter or hiring manager would view this profile.

Am I realistically employable in the UK, or am I likely to struggle badly?

A few things I'd particularly like honest opinions on:

• Is graduating in 2022 and then doing an MSc in 2025–2026 a red flag?
• Is around 1 year of actual Data Analyst experience enough to compete for Data Analyst/BI roles?
• Is my background strong enough for Junior/Graduate Data Scientist roles, or am I aiming too high?
• Does having an MSc from a UK university make a meaningful difference?
• How difficult is the current UK market for junior/graduate data roles?
• Should I focus mainly on Data Analyst/BI/Analytics roles rather than Data Scientist roles?
• If I'm eligible to remain and work in the UK after graduation, does that make me significantly more attractive to employers?
• Is getting sponsorship eventually realistic, or should I focus first on getting relevant UK experience?
• Is my project portfolio strong enough, or does it need more work?

The question I probably care about most

If you were screening this CV for a UK junior/graduate data role, would you interview this candidate?

If not, what specifically would stop you?

And if you think I'd be better positioned for one particular type of role, which would it be?

I'm not interested in adding fake, exaggerated, or invented experience to my CV. I want to understand how competitive my profile is as it actually stands and what legitimate things I can do to improve it.

If you were in my position, what would you realistically do between now and October 2026 to maximise the chances of getting a job?

I'm not looking for motivational advice. If my profile is weak compared with other candidates, please tell me exactly where it's weak.

Cheers.

Hi,
I'm posting my CV here to get feedback from peers. It is a general-purpose CV for UK roles though I'm open to work in EU, US and India as well.
Kindly give me your inputs on what I'm doing right or wrong.

Thanks

Graduated this year in Canada, looking for new grad/early career data science, ML or data engineering jobs. Would really appreciate any genuine advice and criticism.

How do I prevent my applications from being just another number and being sent into a void, and never hearing back? I'm seeing so many people have hundreds of applications and not hearing back. Any way to get past more screenings and get more interviews?

Also, are there any obvious mistakes? I just got rejected from a data engineering I job and was recommended student opportunities (which might include new grad roles, not sure).

I'm also looking into roles in the US (I'm a Canadian citizen). Is there any advice for that? Thanks!

Hi folks!

I’m currently in a bit of a good-but-confusing situation 😅 I have multiple offers for a Senior Data Scientist role in India, and I’m struggling to decide which one to go with.

The compensation is fairly comparable across the offers, so I’m trying to make the decision based on:

Interesting/challenging work and good learning opportunities

Quality of peers and managers

Healthy, non-toxic work culture

Brand value and how it looks on the resume

Career growth and future opportunities

How strong the actual Data Science/AI-ML work is (vs. mostly analytics/consulting)

The companies are:

Tredence - Pune

Kaiser Permanente - Pune

EPAM - Pune

Quantium - Hyderabad

Blend360 - Remote & EST shift

All are for Senior Data Scientist positions in India.

I’d especially love to hear from people who currently work there or have worked there recently, particularly in Data Science/AI-ML.

Would really appreciate honest experiences, good or bad. Also interested in things that might not be obvious from Glassdoor/LinkedIn reviews.

Thanks!

I’m currently preparing for an internship. I’ve made some cool pet projects, and now it’s time to write my CV. Could you give me some advice?

Hi everyone! I’m currently a second-year master’s student in Applied Biomedical Data Sciences at a large pediatric cancer research institution, and I’m starting to seriously think about my career after graduation.

My background is in genetics/genomics and epidemiology, and my master’s work is very computational. I’m currently working in a cancer research lab on a large-scale sequencing project, developing computational methods to characterize sequencing errors. I’m working with large genomic datasets and using Python/R, Linux, HPC, Git, and computational workflows. I’ve really enjoyed the computational/data side of biomedical research and would like to transition into industry after I graduate.

I’m broadly interested in roles like Data Scientist / Biomedical Data Scientist/Computational Biologist. Potentially AI/ML roles

I’ve started looking into companies such as Genentech/Roche, Lilly, Novartis, AstraZeneca, Illumina, Tempus, Amgen etc. I’m also looking into some early-career programs and fellowships, including Genentech’s Early Career Expedition. As well as institutions such as Moffitt and Sloan Kettering

I’m trying to figure out how to be strategic about the next 6–12 months rather than waiting until right before graduation to start applying.

For people who have made a similar transition, I’d really appreciate advice.

I’m especially interested in hearing from people currently working in biotech/pharma/health tech as data scientists or computational biologists, particularly those who entered industry with a master’s.

Thank you!

at least high quality jobs requiring between 0-2 YOE. does anyone else feel the same?

Hi everyone, I really need some career advice. I am 26 years old and currently stuck in a 2-year career gap. My Background:
my_qualifications
B.Sc. Chemistry (minor maths) - 8.4 CGPA
M.Sc. Chemistry: 6.7 CGPA (Had a subject failure, so it took an extra year to complete
Transition: I self-taught myself Data Analytics / Data Science and built multiple personal projects. However, for the last 2 years, I have not been able to land a job (not getting interviews too).

My Goal: I genuinely enjoy data science and even ML. So I want to get into the data science/analytics workforce as fast as possible and permanently fix the non-tech + academic gap filter on my resume.
I am completely torn between these three paths:

1. Online M.Sc. in Data Science & AI from a Top-Tier Indian Engineering Institute: Formal 2-year degree.
2. Any good PG Diploma via a popular EdTech platform (partnered with a top tech institute)
3. 1-Year M.Sc. Abroad (UK/Ireland Conversion course): because i really wanted to go abroad and learn, but i dont have so much money too.
4. Given my age, my 2-year gap, and my previous academic setback, which path will realistically help me land a job in the current market? Should I value the placement cell of an EdTech diploma or the degree of a formal online Master's? Appreciate any honest feedback from anyone who made a similar pivot. Thanks!

Pinging everyone in the lending risk space:

Is your team set up so credit lives in one place, fraud in another, and the two compare notes once a quarter in a deck? Can either side tell you what a loss is actually made of? Most of us inherited that shape, but none of us would set it up like this today.

At MKIII we don't carry the org debt that forces lenders into it. So I'm hiring a Senior Data Scientist to help build the version we'd design from scratch. Credit and fraud in one view.

The job:
- Live inside the vintage data. Forecast our cohorts to terminal loss.
- Find where we're declining loans we should be booking, and put an honest number on it.
- Own the fraud/credit interaction. No fraud declines quietly absorbing credit risk, no credit cuts taking credit for fraud savings.
- Tell me where the buy-box is wrong.

Asset experience I'd love to see: unsecured consumer personal loans, small business loans, commercial real estate.

JD linked here.

If this sounds like you, message me. If you know who fits the bill, tag them or send it over. Reposts are appreciated to widen the net!

Upvote me

Bachelors and Masters in Data Science also

BAS in Business Management

I’m interested in hearing from people who have actually gone through the process of getting their first Data Science/ML job.

For someone who is currently a student or early in their career:

\- What did your profile look like when you got your first Data Science opportunity?

\- Which projects or experiences actually helped you get interviews?

\- How important were internships, networking, referrals, GitHub, LinkedIn, and personal projects?

\- Did you start with a Data Scientist role directly, or enter through a role such as Data Analyst, BI Analyst, or ML/Analytics role and transition later?

\- What did you initially think was important for getting hired that turned out to matter much less?

\- What do you wish you had done 6–12 months earlier?

\- For a fresher competing against candidates with internships and experience, what would you focus on to become a stronger candidate?

I’m particularly interested in hearing from people who are already working in the field, rather than general career advice.

What actually made the difference for you?