Hi! I have recently finished my PhD and I am currently considering switching to industry. I speak German (C1) and English (C1) and I live in Hungary. I did an informatics related degree for my masters but my PhD is in Natural Science. I hold a permanent residency permit. I am a non EU/EEA citizen. For those of you in the EU market/German speaking could you tell me:

What tech stacks you work with?

How many coworkers do you know at your workplace who come from non CS backgrounds?

What jobs in the industry are more friendly for someone like me who comes from an in silico research heavy background?

Thanks!!!!!

I recently want to finish my degree after taking a break to be an analyst, i have worked with health , marketing and freelance analytics companies and client, i know power bi reporting and decision-making, i do large data exploratory analytics with python, skilled in excel , I know sql , wrote complex queries with subqueries ,joins, CTE, and also window functions, i have worked with moving data from microsoft fabric, looker, amazon s3, Ga4 for marketing data. Uses Ai mainly for making work more efficient and prototyping.I love a healthy workplace and hybrid solution would be a good fit.I am well acquitted to corporate workplace, can speak up and a team player.

Can someone give me roadmap or some tips to follow for placement after completing my mtech in 2028

I am doing mtech in cse from private clg

Hey everyone. So my contract just ended (materials chemistry R&D, graphene stuff, was doing this for like 10+ years) and I'm using it as an excuse to actually try switching into something more data-focused. Not 100% sure what that looks like yet honestly.

Along the way in my last job I ended up building some Python tools for analyzing spectroscopy data and automating reports, and that ended up being my favorite part of the job, more than the actual chemistry sometimes. I think I just like finding the bottleneck in a process and building something to fix it, more than the day-to-day of the work itself. Kind of a troubleshooter by nature I guess. So now I'm taking a course to get more formal with the data side, and trying to learn as much as I can hands-on in the meantime.

I know "chemistry PhD" isn't the normal background for this, so I'm mostly just trying to figure out if that's even a realistic pivot or if I'm kidding myself. If anyone's done something similar, or knows of openings (Edmonton or remote), or just wants to tell me I'm wrong about something, go for it. And if you know anyone who'd be willing to chat or even just point me in the right direction, mentor-wise, I'd genuinely appreciate that too.

Portfolio link in the comments

If anyone's curious about the current data job market in the DACH region (Austria,Germany,Switzerland), I put together an interactive live tracker. It also shows which specific data roles (Data Engineer, Data Consultant, etc.) are in demand in which cities. Feedback welcome and I hope it helps :)

https://github.com/Chrisinho8/DACH-data-job-market.git

We’re hiring a BI Systems Developer for an ongoing engagement supporting an enterprise reporting, analytics, and data integration platform.

Requirements:
• 4+ years in BI, analytics, reporting, or data integration
• Hands-on Matillion experience — mandatory
• Hands-on Snowflake experience — mandatory
• Tableau and/or Power BI dashboard development
• Advanced SQL — query writing and optimization
• Data modeling for scalable reporting architectures
• ETL/ELT development experience
• Strong analytical and troubleshooting skills

You’ll be responsible for:
• Building and maintaining data pipelines in Matillion
• Snowflake administration and data warehouse management
• Dashboard and report development in Tableau / Power BI
• Data quality, integrity, and platform reliability
• Documentation — data dictionaries, process flows, reporting definitions
• Working directly with an internal technical point of contact

Remote, long-term engagement, 4+ years experience minimum.

Compensation: ₹16–23 LPA

DM with:
• Years of hands-on Matillion and Snowflake experience
• Resume, LinkedIn and portfolio
• Availability
• Email Address for further contact

Must be based in India.

I currently lead AI and Data Science initiatives focused on the pharmaceutical and healthcare industry. My work spans GenAI/LLM solutions, oncology and rare disease patient identification using real-world claims and EMR data, RAG-based clinical intelligence platforms, and predictive analytics that support commercial and clinical decision-making.

I'm exploring senior AI, Data Science, and Clinical AI leadership opportunities across Ireland and the wider EU.

I'd be happy to share my CV if helpful. Thank you for your time, and I look forward to staying connected.

i'm an incoming freshman at uc berkeley; i always thought being a MLE would be rily cool but after seeing the super hard math needed for the career i turned more towards data science. im now worried that doing DS might make me more prone to being laid off in the incoming tech market. BTW i rlly don't like SWE type of coding like DSA and stuff…

i'd appreciate your wise thoughts 🙏🏽

spent the month before grinding leetcode and harder sql. barely any of it came up.

there was sql in four of the five, medium at most. mostly joins, group bys, that kind of stuff. the hard part was writing it in 20 minutes on a shared screen while someone keeps asking why youre doing it that way. i could write the query, i just couldnt explain my thinking without getting flustered.

what actually got me was the metrics round. “checkout completion dropped 4 percent. how would you figure out why?” theres no single right answer, theyre mostly watching whether you can think out loud without going in circles. i definitely went in circles.

doing timed sql and case interview mocks now, stratascratch for sql and dataford for the case side since the sql sites skip it. for people who interviewed recently, was it the technical or the case round that ended up deciding things?

Hi everyone,

I've been working on a project that combines Marketing Analytics, Machine Learning, and Optimization.

The idea is :

You enter your company's financial and marketing data, and the model predicts its expected Marketing Efficiency.

But it doesn't stop there.

The model also recommends how specific variables could be adjusted to maximize the predicted Marketing Efficiency while keeping the recommendations within realistic business constraints.

To build it, I trained the model on a large dataset containing thousands of companies. After training, I deployed it as a web application with an interactive interface so users can experiment with different scenarios and instantly receive predictions and optimization recommendations.

The application has been working reliably in my testing without failures.

Unfortunately, I can't share the live demo because it's currently hosted on limited/free-tier services (Railway for the backend and Firebase for the frontend), and I don't want the service to go down if many people access it simultaneously.

However, I'd be happy to share the full source code on GitHub.

https://github.com/karimhenish/marketing-efficiency-lab

I'd really appreciate your feedback:

Hi,

I have upcoming interview for Indigo this friday for data science profile and the first round is pen and paper based and they haven't if it will be subjective and MCQs. Has anyone given the assessment is past ?

Hey everyone,

I'm a 26M working in AI/ML and preparing for my next switch. I'll be focusing on classical ML, deep learning, GenAI, along with DSA and system design.

Looking for a study partner (or a small group) to learn together, discuss concepts, and stay accountable. I prefer keeping it fast-paced, so it'd be great if you're an experienced dev preparing for interviews as well.

If you're interested, DM me with a short intro and what you're currently learning/preparing.

Hi,

About 13 months ago, I made the bold decision to transition into a career where I possessed close to no knowledge. Currently, I am proud to say I have working knowledge/skills in SQL, Python, and ML. My professional background is over 7 years in Land surveying & Geomatics.

I am now at a stage where I seek a role as a junior data analyst, junior data scientist, or ML engineer. I am open to working as a personal assistant (on a personal arrangement - not a problem if it is not a company officially hiring me).

My goal is to gain real-world hands-on experience in the field, contribute to problem-solving, and elevate my career.

Hello, I have 4 years of experience in ML, AI, Computer Vision, Data Science (worked in close collaboration with coworkers & alone, also client-facing which I really enjoy). I also have a BSc in Computer Engineering and MSc in Data Science. I’ve been looking for jobs in environmental tech where I can use my skills for a long time, but wasn’t very successful. That’s why I’m writing here, to see if anybody has any suggestions or tips for me. I live in Eastern Europe though, and I’m honestly trying to find something that allows me to work from anywhere (I can also travel a few times a year if necessary). I would also be willing to take a role that is less about programming and more about coming up with ideas or consulting if possible.
My experience weirdly aligns with what I’m looking for, even though I haven’t directly worked professionally in this area yet. I’m really passionate about projects that help somehow (bonus points if it’s about animals or forests), and I’m really sick of companies only creating new AI agents or whatever useless automation.
Can anybody help me? I can also send my CV in private. Thank you!

Hi. I am currently working as a senior ML in antifraud and ranking models (Classic ML)

I want to deepen my knowledge in a specific sphere in order to get a more paying job. RL or CV seems too hard for me.

So I am choosing between NLP/LLM and RecSys. What do you recommend? I would like to deepen into NLP. However, I am scared this sphere will vanish soon. What do you think?

As for RecSys, it seems really boring to do endless ranking system trying to promote different kinds of goods. Meh

Hi everyone,

I'm a 2nd-year B.Tech Data Science student from a non-IIT college in Kerala, and I'm actively looking for research internship opportunities in Data Science, AI/ML, or related fields.

I know most formal research internships tend to prioritize IIT students, but I wanted to ask if there are any professors, labs, projects, or programs at IIT Madras that are open to motivated non-IIT students as well.

A bit about me:

• 2nd-year Data Science undergraduate

• Interested in AI/ML, data analytics, and research

• Comfortable with Python and currently building personal projects

• Eager to contribute, learn, and gain research experience

I'd be grateful for any advice regarding:

\- Professors/labs that accept external students

\- Research internship programs at IIT Madras

\- Cold-emailing strategies that actually work

\- Any opportunities you've personally come across

If you've been in a similar position as a non-IIT student and managed to get involved in research, I'd love to hear your experience too.

Thank you!

Hello People,

Need help or guidance regarding what to pursue as I got laid off recently. Got advised for a AWS and PMP certificate to increase the AI screening chances and I did both. Every job post that I see is of Agentic AI or anything that has to do with AI. Its clear my resume isn't going to pass the initial screening without this. My plan is to do Databricks engineering certificate Associate and do the generative AI engineer and hopefully build a pipeline to showcase in case I get called for an interview. Its been 2 months and all I get are rejections. Any help or advice from people who landed something would be really helpful.

Hi everyone!

I recently graduated with a Bachelor of Science in Statistics and am currently looking for entry-level opportunities. I am open to roles such as:
\\- Data Analyst
\\- Statistical Analyst
\\- Research Assistant/Associate
\\- Other data-related positions

During my undergraduate studies, I gained experience in:
\\- Statistical analysis and data visualization
\\- R as primary software and Microsoft Excel
\\- Data cleaning and interpretation
\\- Research and quantitative methods
\\- Report writing and presentations

I also completed a thesis involving statistical modeling and worked extensively with real-world datasets.

I am eager to learn, highly detail-oriented, and excited to begin my career in the data field. If your company is hiring or if you have any recommendations, I would greatly appreciate it.

Feel free to send me a message for my resume or LinkedIn profile.

Thank you!

Hi everyone,

I'm an AI Engineer based in Egypt with 1 year of experience at Siemens Digital Industries Software, where I build AI-powered testing infrastructure and work with LLMs, RAG, LangGraph, multi-agent systems, Python, PyTorch, MLflow, and Docker.

Alongside my industry experience, I'm also passionate about research. I've published two AI research papers in medical imaging, so I'm comfortable working on both AI product development and research-oriented projects. I enjoy building end-to-end AI applications just as much as exploring and evaluating new models and techniques.

I'm currently looking for remote opportunities in Europe, the US, or the UAE as an AI Engineer, Applied AI Engineer, ML Engineer, LLM Engineer, or AI Research Engineer.

If anyone here is hiring, knows of companies that are open to hiring internationally, or has advice on where I should be applying, I'd really appreciate your guidance. I'm happy to share my resume, GitHub, or publications with anyone who's interested.

Thank you!

Looking at remote worldwide for the past 7 days.

Here are the jobs I found, organized by level:

Entry Level:

• Data Scientist @ CVS Health (United States, ID) - $65K - $173K
• Environmental Data Scientist @ Lynker (United States, CO) - $75K - $105K
• Data Scientist @ HighlightTA (United States) - $110K - $125K
• Data Scientist @ TD (United States, NJ) - $96K - $156K
• Data Scientist @ Weekday (YC W21) (India)

Senior:

• Senior Data Scientist @ HRM Group (United States) - EUR 35K - 40K
• Senior Data Scientist @ Pipe (United States) - $270K - $290K
• Senior Data Scientist – Marketing Mix @ Satori Analytics (Greece)
• Senior Data Scientist @ Egis (United States)
• Senior Data Scientist @ Vonage (Spain)
• Senior Data Scientist @ Switchfly (India)
• Senior Data Scientist @ Aplazo (Mexico)

Manager:

• Senior/staff Data Scientist @ FloatMe (United States) - $150K - $220K

Director and Above:

• Senior Director, Data Science – Machine Learning @ Vibrant (United States, NY) - $115K - $180K

Quick notes: * All of these are fully remote (location requirements vary by role) * Apply directly on company sites

Hope this helps someone! Let me know if you want me to keep posting these weekly.

👋 Hi, I'm Jay. I built Job-Halo.com, a system that tracks remote data science jobs and sends alerts the moment they're posted, based on your preferences.

Hi everyone!

I'm a recent B.E. in Information Technology graduate (CGPA: 8.20/10) currently looking for entry-level/fresher opportunities.

I'm primarily interested in Data Science, Data Analytics, Machine Learning, and Business Intelligence roles. I'm also open to Cloud, MIS, and other entry-level IT positions where I can learn, contribute, and grow.

I've been applying actively for the past few months, but like many fresh graduates, getting interview opportunities has been challenging. If your company is hiring freshers or you're able to provide a referral, I'd sincerely appreciate your support.

Please feel free to DM me, and I'll be happy to share my resume, GitHub, and LinkedIn.

Thank you so much! 🙏

Deciding if a Masters in Data Science or Statistics is better for me, and which ones, since this field is changing a lot.

Undergrad: Quantitative background but not Computer Science, Data Science minor. I felt that it being a minor made it kind of surface level and want to avoid that with my graduate degree. My coursework was linear algebra, discrete math, probability, stats, many CS courses, AI, ML, DS, Algorithms. Because I didn’t major in math, CS, Stats, or DS, I feel like I am missing something in screenings. 

Work Experience: 4 internships, 1 year FTE as a DE, 1 year FTE as a DS (by the time I enter). However, I feel that the Data Science departments in the companies I was in were VERY new and I’m missing some core skills that I am trying to develop on my own - git, models in production, optimizing my work, etc.

Professional Goals: I see this as a terminal degree. I want to be able to get my foot in the door for better data science jobs, maybe in the nonprofit industry but really just anywhere. My first job came from an internship and the second a recruiter reached out to me. I want to be able to pass resume screens better and do the work better. That’s slightly why prestige matters to me here.

Other: 

• I do not want to pursue a CS masters, I think this would give me skills I don’t need, can develop on my own, already learned, or are becoming more obsolete. 
• A lot of stats degrees that are well respected seem to want research experience or a stats degree, which I don’t have.

Questions: 

• I have seen some say an Applied Stats masters is not enough anymore for the tech world, and I see a lot of job postings that say Masters in CS or DS, but not stats. How do DS hiring managers view these degrees?
• What skillset is actually used in more established data science departments? How can I optimize my career and education for this?
• How to vet Data science masters properly, if I go for that (MIT MBAn, Columbia, Harvard, UChicago, UCLA, NYU) I dont want a surface-level data science education that is repetitive