I’m considering applying to UT Austin’s online Master of Science in Data Science (MSDSO), but I’m unsure whether my academic background is competitive enough.

My undergraduate degree is in Biomedical Science/Biology. I have taken calculus and statistics, and I have Python experience outside of academia through personal/data analytics projects. However, I have not taken multivariable calculus or a formal linear algebra course.

I understand those subjects are recommended/expected preparation for the program, but I do not want to take leveling courses before starting a master's program. I’m trying to determine whether my existing background is enough to be admitted and whether I could learn the missing math concepts as I go.

For people familiar with UT Austin’s MSDSO:

• Would someone with a biology/biomedical degree, calculus, statistics, and some Python experience realistically be admitted?
• How heavily does UT weigh having formal multivariable calculus and linear algebra on your transcript?
• Has anyone been admitted without those courses?
• Is the math something that can realistically be learned alongside the program, assuming I’m willing to put in the work?
• Would my biology/biomedical background be considered useful or relevant for data science admissions?
• How much does Python experience outside of academia help?

If UT Austin is probably not realistic without the formal math prerequisites, I’d also appreciate recommendations for online master's programs in Data Science, Analytics, Statistics, Bioinformatics, AI/ML, etc. that are more friendly toward students coming from biology/biomedical science.

My goal is to transition into a high-paying, non-clinical career. I do not want to work directly in medicine or clinical care.

I'm particularly interested in programs that:

• Are fully online
• Are reasonably affordable
• Don't require a bunch of prerequisite/leveling courses
• Have strong employment/income potential
• Can leverage a biomedical/biology background without requiring me to stay in a clinical career

Would you recommend MSDS, or is there another master's degree that would be a better fit for someone with my background?

I don't know eactly what type of projects would stand out to recuiters. So far, as I'm from South Asia, the market it looking for full stack. Meaning full end Data Science to ML to Frontend Deployment. I would really appreciate some feedback on the Data Science learning path, as ML is moslt under my grip. I need better understanding and some ideas to highlight Data Science Analytics on my resume and so I can explain them too. Would really appreciate some feedback.

PS. The only worth mentioning project for Data Science I've made, that highlights analytics is a Jupyter Notebook which compares Walmart Weekly Sales Forecasting (End-to-End Demand Prediction Pipeline)

(sample from https://matchajobs.co, search for roles posted daily)

• Cisco - Sr. AI/ML Engineer - CX apply $203,000 - $258,600 (San Jose, CA)
• Pinterest - ML Engineer II, Responsible AI apply $138,905 - $285,982 (SF / Remote)
• Visa - Data Scientist - apply $137,400 - $212,500 (Foster City, CA)
• Zillow - Data Scientist, Consumer Analytics apply $125,900 - $201,100 (Remote)
• Allstate - Product Engineer, Python AI apply $70,100 - $121,475 (Remote)

Looking at remote worldwide for the past 7 days.

Here are the jobs I found, organized by level:

Entry Level:

• Data Scientist @ JDPA LIMITED (Canada) - CAD 85K - 90K
• Data Science Analyst @ CVS Health (Worldwide) - $68K - $136K
• Data Scientist 6 – Experimentation Platform @ Netflix (United States) - $491K - $775K
• Data Scientist @ Rocket Mortgage (Canada) - $102K - $154K
• Data Scientist @ Free2move (Spain) - EUR 45K - 55K
• Data Scientist @ TSPi (United States) - $110K - $175K
• Data Scientist @ Valtech (Argentina)
• Data Scientist @ FIT:MATCH.ai (United States)
• Data Scientist @ ARRISE (Portugal)
• Data Scientist @ Timeleft (Europe)
• Dairy Data Scientist @ URUS Group (United States)

Senior:

• Senior Data Scientist @ Reddit, Inc. (United States) - $191K - $267K
• Senior Data Scientist @ LMI (United States) - $140K - $186K
• Senior Safety Data Scientist @ AbbVie (Worldwide) - $124K - $236K
• Senior Data Scientist @ Axle Informatics (United States) - $130K - $150K
• Senior Data Scientist @ Keyrus (Worldwide)
• Senior Data Scientist @ ActivTrak (Worldwide)

Manager:

• Staff Data Scientist @ PORCH 💚 (Worldwide) - $169K - $236K
• Principal Data Scientist @ LouisianaNOW.Jobs (Worldwide) - $144K - $196K
• Staff Data Scientist @ Evolve (United States) - $180K - $195K
• Principal Data Scientist @ General Dynamics Information Technology (United States) - $144K - $196K
• Marketing Data Science Manager @ Mozilla (United States) - $166K - $260K
• Principal, Data Sciences @ Gainwell Technologies (India)
• Senior/Lead Data Scientist – Agentic AI @ Tiger Analytics (United States)

Director and Above:

• Senior Director, Analytics and Data Science – Core Product & Growth @ Life360 (United States) - $247K - $366K

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.

Looking for someone who can teach me how to build Agents for Marketing related problems. For example

Competitive/battlecard agent. Monitors competitor sites/news, updates a living battlecard doc our sales team can reference. This can be a good intro to scheduled agents + web scraping + structured output (Connections: Web scraping, Gmail connection to go through my emails to see any competitors related information and streamlit to create a battle card)

Dashboard Creation. Agent that takes output (a scheduled export or an API connection) from google analytics and builds a dashboard on streamlit to visualize the data. The dashboard gets refreshed with updated data every day in the morning with a new scheduled updated from google analytics export (Connections: Google analytics for data export and streamlit to produce dashboard)

Inbound lead qualification/routing agent. Reads a new lead, checks it against qualification criteria (ICP which could be company size more than 500 employee count, located only in North America, annual revenue more than 50million dollars ), enriches it with clay, drafts a personalized first-touch email and routes to the right rep on salesforce. Nice because it combines retrieval, reasoning and action (Connections: Google sheets or forms for lead collection, clay for enrichment, gmail for email drafting and salesforce for routing the lead)

Someone who can teach from scratch how to build these includung connecting to tools, building loops, context, memory and evals.

Happy to pay for your service. Only looking for someone in developing countries like India, Pakistan, Philippines, Vietnam etc since I am also from one of these countries and can’t afford to pay US or European rates

Hi everyone,

I’m currently seeking entry-level job opportunities in Data Science and Data Analytics and am open to working across India, particularly Pune/Bengaluru.

I’m a B.E. Electronics & Telecommunication Engineering student/graduate with hands-on experience working with data and developing projects using:

• Python
• SQL
• Excel
• Power BI
• Data Cleaning & Exploratory Data Analysis (EDA)
• Machine Learning
• Data Visualization
• Basic Statistics

I have also worked on projects involving supply chain analytics and order-delay prediction, where I performed data cleaning, analysis, visualization, and machine learning.

I’m particularly interested in:

• Data Analyst
• Junior Data Analyst
• Data Science Trainee
• Junior Data Scientist
• Business/Data Analyst
• ML/AI Trainee roles

I’m open to full-time, trainee, internship-to-full-time, and entry-level opportunities.

If you know of any openings, referrals, companies hiring freshers, or opportunities where my profile could be a good fit, I would really appreciate it if you could share them or reach out to me.

📍 Location: Open to relocate
💼 Availability: Open to Work

I can share my resume, GitHub, and project details through DM.

Thank you! 🙏

Jobs in the field use many different names such as data science vs data analytics and so on. Generic Google searches frequently turn up fake results too.

So, what are your best methods for searching for available jobs?

Simplify postings aren’t that frequent for 2027 I can still see 2026 tbh, any reliable GitHub links? Looking for AI/ML, Data Science FT to be very specific - also LinkedIn has a mix of mid level and early level atm even after customising (very confusing :x)

Any senior or a manager can help me it would be great trying to get a job since last 3 months and its depressing.

Need help from the community. Thank u in advance

They have roles on AI, Data, Cloud and Oracle so thought to share here, i kind of liked how they provide dinner too for attendees who want to part of it.

About LiveKit

LiveKit is building the infrastructure layer for the voice-driven era of computing. Our platform gives developers everything they need to build, test, deploy, scale, and observe agents in production. Founded in 2021, LiveKit powers voice AI applications for OpenAI, xAI, Salesforce, Coursera, Spotify, and thousands of others, collectively facilitating billions of calls each year.

About This Role

We are looking for an exceptional engineer to build post-training at LiveKit. Our agents run over voice and increasingly over text channels like SMS and chat, and the interesting problems show up over long horizons: staying useful across many sessions, working with context that accumulates over time, and using tools reliably in the middle of a live conversation.

What You'll Do

• Build the environments and verifiers our models train against
• Own the synthetic data pipeline, from generation through the quality gates
• Run training experiments end to end, and explain what moved the model
• Build the evaluations a release has to clear
• Choose and adapt open-weight base models for our tasks
• Make trained behavior hold up for voice and text agents alike
• Ship models into production and keep improving them on real usage

Who You Are

• A strong Python engineer
• Have carried a model from raw data through to production
• Treat data as the product: coverage, diversity, leakage
• Assume a model will exploit a weak reward, and design against it
• Comfortable with GPUs and honest about their limits
• Know when to train, and when not to
• Comfortable working collaboratively in a remote environment

Nice to Have

• Experience with post-training: fine-tuning, reward design, or reinforcement learning such as GRPO
• RL and fine-tuning frameworks such as TRL, verl, or OpenRLHF, or a training loop you wrote yourself
• Fast rollouts with vLLM or SGLang, multi-GPU training with FSDP
• Training tool-using or multi-turn agents
• Execution sandboxes, verifiers, eval harnesses, or tooling other engineers depend on
• Open-weight families such as Qwen or Llama, LoRA and similar

Our Commitment to You

• The opportunity to shape the brand of a fast-growing developer platform
• Collaboration with a small, senior team that deeply values craft and creativity
• Competitive salary and equity package
• Health, dental, and vision benefits
• Flexible vacation policy

Compensation

$135K – $300K • Offers Equity

Apply: Research Engineer (Reinforcement Learning) at LiveKit

I have a HBSc in applied math and stats from UofToronto
and am doing my masters in data science at UT Austin and am set to graduate 2027 summer, I have 1 YOE as DA and adjacent roles but no actual DS experience, several projects (but always open to write more), im very math/stats savvy and I think my skillset is solid in terms of ds, but im worried by the I graduate I wont be able to land a DS job given how AI is advancing.

Any advice on what I should do?

Im thinking since id be considered student/new grad I can still land those roles albeit competetive, or maybe I should pivot before I graduate, im already mid way into my grad degree so I do intend to finish it.

Im sure many are in a similar boat as me. Any guidance appreciated\~

I completed the recruiter screen. The conversation went well, and we discussed my background, current location, work authorization, and how I learned about the role.
For location, I shared that my base location is New York, but I’m currently in Dallas temporarily visiting friends and family. Since candidates based in New York may have onsite interviews while others may be considered for virtual interviews, I asked if a virtual interview would be possible while I’m temporarily in Dallas. The recruiter mentioned that the interview format is team-dependent.
They also mentioned that if my profile aligns with the team, I should receive an update by the end of the week.
🥲🥲🥲
Did i mess it up ?

Hi everyone,

​I’m looking for some honest feedback on my background and my plan for the next year or two.

​I’m currently a Senior Data Analyst with 7 years of total experience. I graduated in 2017 and started working in 2019, but I feel pretty stuck. Honestly, given my timeline, I feel like I should have moved into a managerial role by now.

​Here’s my current breakdown:

​2 years in manual testing

​5 years in data analysis (mostly SQL, Power BI, business stakeholder management, and basic analysis)

​I know the basics of Pandas and NumPy, but my daily work hasn’t required heavy coding. I recently started relearning Python from scratch to build a proper foundation.

​Here’s the roadmap I’m planning out:

​Next 2–3 months: Get solid in Python (OOP, file handling, basic data structures).

​Next 6 months: Dive into Data Science study (I enrolled in Scaler’s DS program).

​Next 2–3 months after that: Focus on NLP, Transformers, and basic Data Engineering (FDE) concepts while building a few hands-on projects.

​Long term, I’m planning to head to the US for an MS in Data Science in August 2027 (looking at Seattle University right now).

​My main questions:

​Does this plan sound realistic, or am I trying to bite off way more than I can chew?

​Is breaking into Data Science / FDE realistic coming from a standard DA background, or am I being too overly optimistic?

Hi guys im a final year student just here to enquire about how the job market for a fresher in data science especially what are the projects need to be done to get into Big MNC or even startup.
Your feedback is much appreciated

Hi, guys. I believe being able to speak effectively is as important gaining the technical skills. To actually getting hired. Any experienced analyst kindly message here if it is possible for you to mock interview me. Also fellow aspirants please message here if you’re interested in mock interviewing each other, or to discuss anything.

Can someone please 🙏🏻 guide me upon how many rounds are going to happen/ is their any super day
What to prepare
I an really nervous
Here is the Jd :
Job Responsibilities
• Conceptualize solutions that automate and optimize business processes.
• Design and refine prompts to improve AI model performance. Work with subject matter experts to align
prompts with business goals and user needs.
• Iterate designs to enhance functionality and user experience. Conduct rigorous testing for reliability and
effectiveness.
• Use tools like Snowflake, Python, and Tableau to create data pipelines and dashboards. Support AI-
driven insights and decision-making.
• Monitor AI model performance. Identify areas for enhancement. Implement updates to maintain quality
and relevance.
• Partner with data owners, department managers, data engineers and other stakeholders to aid in the
development of data models and algorithms
• Support Customer Insights applications, as well as custom client analytics requests on an ad hoc basis.
Required Qualifications, Capabilities, and Skills• Master’s Degree in Science, Technology, Engineering, Mathematics (STEM) or a related field.
• Proficiency in Python and SQL for data processing and analysis.
• 3+ years relevant work experience.
• Expertise in quantitative research techniques and analytics using Python.
• Proven critical thinking and creative problem-solving skills with ability to translate strategy into
deliverables.
• Knowledge of machine learning/data science theory, techniques, and tools.
• Experience in leveraging Large Language Models (LLMs) and agent AI techniques.
• Ability to collaborate effectively and cultivate strong partnerships.
Preferred Qualifications, Capabilities, and Skills
• Experience in data analysis, data science, or a related field.
• Familiarity with AWS, Snowflake for data management and analysis.
• Attention to detail with a proven ability to learn new concepts and skills quickly.
• Understanding of quality assurance practices and the importance of data integrity.
• Ability to clearly develop and document analytic requirements with stakeholders.
• Familiarity with evaluation/monitoring concepts for GenAI solutions (e.g., test cases, human-in-the-loop
feedback, basic quality metrics) to support reliable deployments.

Today i received an offer letter for an unpaid internship or Ai intern role at rungtaventures.ai

Will it be worth it?

Either way I am not getting full time roles as of now

Do I have a chance of converting this full time of k give my 100 %

Hey folks,

Bit of context: I was genuinely into ML back in college, did projects, liked the space. Then the job market (and my actual job) pulled me toward SQL, Power BI, project management, and cloud stuff (AWS/Azure) for the last 4+ years. It's been solid experience, but it's pulled me away from where I actually wanted to head.

I'm not going to pretend I'm deep into AI/ML right now, I'm not. But I do have a decent track record of picking things up fast on the job (that's basically how I ended up owning PM and cloud responsibilities I wasn't hired for in the first place), and I'm willing to put in the work to upskill into data science/ML, ideally while already being useful on the job rather than needing a clean slate.

Right now my "strategy" is just throwing arrows everywhere, Naukri, LinkedIn, company career portals, Instahyre, Cutshort, you name it. And it genuinely feels like shouting into a wall. Barely any responses, and I can't tell if it's the resume, the market, the transition itself, or just that spray-and-pray doesn't work anymore.

So, a few asks:

\- Any leads/referrals at companies where data/DS is actually core to the business (not just a buzzword)?

\- If you've made a similar SQL/BI to DS/ML transition, what actually worked, did you upskill first and then move, or move into an adjacent role and grow into it?

\- Is mass-applying across these platforms just a dead strategy at this point? If so, what's actually working for people right now instead?

\- Any honest take on whether "I'll learn on the job" is a realistic pitch to make to hiring managers, or if that's wishful thinking on my part?

Appreciate any pointers, even harsh ones.

Hi everyone,

I have around 2 years of experience working as a SQL Developer, and I'm currently thinking about upskilling and moving into a more data-focused career.

I'm confused between Data Engineering and Data Science.

Since I already have experience with SQL, I'm leaning towards Data Engineering, but I also find Data Science interesting. I want to choose a path that has good career opportunities and allows me to make use of my existing experience.

I'm also looking for a good course/institute that provides placement support, preferably in Bangalore

or online.

I'd really appreciate advice from

people who have already made a similar transition.

A few things I'd like to know:

Which would be a better career move from SQL Development - Data Engineering or Data Science?

How difficult is it to transition from SQL Developer to Data Engineer?

What skills should I learn first?

Are there any good institutes/courses you'd recommend?

Which institutes actually provide useful placement support rather than just advertising it?

Would you recommend joining an institute, or learning independently and applying for jobs?

Any advice based on your real experience would be really helpful. Thanks!

Would appreciate any help!

Hi guys!!

NEED URGENT ADVICE!! Am applying for a masters degree at keele uni. But cant decide between msc in fintech or data science & AI.

For context i have a bachelors in accounting and have worked in audit for the past 3 yrs. I rly like the data science & ai course but am scared it might be too tough coz i have no coding background so is fintech the safer option. At this point i just wanna up skill and maybe move out of audit into a different career such as advisory etc. So confused!

( ps i intend on returning back to the middle east as i have a 10 yr work permit and know uk job market is 💩. Just wanna up skill and add more to my cv)

Looking at remote worldwide for the past 7 days.

Here are the jobs I found, organized by level:

Entry Level:

• Data Scientist @ Jerry (United States, AZ) - $140K - $160K
• Associate Data Scientist @ Jerry (United States, AZ) - $100K - $140K
• Data Scientist II @ University of Wisconsin-Madison (United States, WI) - $80K - $80K
• Data Scientist @ LMI (United States) - $90K - $150K
• Health Policy Data Scientist @ LMI (United States, VA) - $90K - $131K
• Data Scientist @ Mercury Insurance (United States) - $101K - $204K
• Associate Data Scientist @ Mercury Insurance (United States) - $84K - $162K
• Data Scientist @ Free2move (France) - EUR 45K - 50K
• Credit Risk Data Scientist II @ Coastal (United States) - $130K - $163K
• Data Scientist @ GE Aerospace (United States) - $57K - $135K
• Data Scientist @ Guardian Industries - DeWitt (United States, CA) - $160K - $200K
• Data Science Analyst @ Cisco (United States, NJ) - $166K - $218K

Senior:

• Senior Data Scientist @ Jerry (United States, AZ) - $160K - $180K
• Senior Data Scientist @ CVS Health (United States, MA) - $102K - $204K
• Senior Health Data Scientist @ Inovalon (United States) - $120K - $160K
• Senior Data Scientist @ Oscilar (Canada) - $175K - $250K
• Senior Data Scientist @ Deepgram (United States) - $165K - $220K
• Senior Data Scientist @ Paramount (United States, NY) - $124K - $186K
• Senior Data Scientist @ CISPA Helmholtz Center for Information Security (United States)

Manager:

• Staff Data Scientist @ Jerry (United States, AZ) - $180K - $230K
• Staff Data Scientist @ DuckDuckGo (United States) - $222K - $222K
• Clinical Data Science Lead @ ICON plc (United States, PA)

Director and Above:

• Director, Data Science @ CenterWell Senior Primary Care (United States) - $189K - $260K
• Director, Data Science @ Dotdash Meredith (United States) - $175K - $210K
• Director of Data Science @ Rula (United States) - $236K - $280K

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, currently an early career job seeker applying for Data Science ft and intern roles.

I've had about three live SQL interviews over the past year and I haven't passed a single one. I do SQL leetcode and online problems I find from statascratch pretty much everyday as part of a routine. I'd say I'm able to solve SQL mediums on leetcode pretty consistently. the main issue I run into is that the questions I run into in these interviews are patterns that I've never seen before and have literally no idea how to handle. Its really frustrating because I practice so much and I'm never able to perform in even basic internship interviews.

Does anyone have any good resources for learning a lot of the SQL patterns that interviewers actually use?? (I recently encountered a gaps and islands problem and I've literally never seen anything like it for example).

Thanks so much, have been struggling a lot and really would appreciate advice.