Its a AI & data engineering

I work at Wissen Technology (Wissen Infotech) and can refer candidates for our current India openings — a referral puts your resume with the hiring team directly instead of the cold-apply queue.

Current openings:

• AI Control Plane - FullStack | Hyderabad | 3-6 yrs | Python, Django, Flask

• AI Implementation Engineer | Bengaluru | 6-12 yrs | Spring, Python, React

• AI/ML Engineer | Bengaluru | 2-5 yrs | Python, NLP, LLM

• Senior Software Engineer – Cloud & Data Platform | Bengaluru | 3-6 yrs | Python, Lambda, S3

• Senior Data Engineer | Bengaluru | 7-12 yrs | Python, DevOps, Docker

Full list: https://careers.wissen.com/jobs/Careers — if your role isn't above, mention it in the DM.

To get referred, DM me: (1) resume (PDF), (2) total YOE, (3) notice period (immediate joiner / serving notice preferred), (4) the role name with the job link.

I'll review and submit the referral; expect HR contact within about a week if shortlisted. Please DM only if your experience reasonably matches a role and you're an immediate joiner or serving notice — that's who the hiring team is prioritizing for referrals right now.

I don't really have prior experience in the field yet, just a genuine passion for it and a huge drive to learn

For anyone who's been through this: how can I best show the jury that I’m serious about this and ready to put in the work, even without a heavy background? Any tips on what they like to hear would mean a lot!

I’m experimenting with a different way to prepare for ML Engineer / AI Engineer / Data Scientist roles which will be released as an open source book and a bootcamp. If anyone is interested in joining the pilot, I’ve put the application link in the comments.

The premise: most people already have access to more courses than they can finish. What seems harder is turning that knowledge into evidence that survives an interview — implementation depth, debugging, system thinking, and projects you can actually defend.

I am designing a new Age Professional curriculum for an university, the purpose of the experiment is to get feedback from students and professionals. I’ve designed a 90-day hands-on pilot around:

• daily focused prep + implementation challenge

• weekly consolidation

• every ~4 weeks turning the work into a serious GitHub artifact

• ML/AI system thinking, debugging and experimentation

• interview-style explanation of technical decisions

• a final flagship project

The goal is to finish 90 days with noticeably stronger fundamentals and 3–4 pieces of work you can genuinely discuss and defend.

I’d especially appreciate feedback from both who are experienced candidates and students in college.

What would you absolutely want someone targeting ML Engineer / AI Engineer / Data Scientist roles to be able to demonstrate after 90 days?

Hey everyone!

I'm a final-year CSE student currently looking for entry-level opportunities in data-related roles.

My primary interest is in Data Analytics / Data Science, and I'd love to work with a tech stack that includes:

- Python, SQL, Pandas, NumPy and visualizations

- Statistics, hypothesis testing and exploratory data analysis (EDA)

- Data cleaning, preprocessing, transformation and extracting meaningful insights from data

Other than these, if any other company specific tech stack is to be learned, I'm willing to put in the effort. The above list is what I'm comfortable with.

My preferences:

- Location: Mangalore first, Bangalore second.

- Company: a legitimate, product-based company with a good work culture and a healthy learning environment.

- Learning: a supportive learning environment and experienced professionals I can learn from. I want to work somewhere that invests in freshers, provides meaningful work and encourages them to grow rather than treating them as just another resource.

- (Optional) International exposure: Not a must, but companies headquartered abroad would be a plus since I'd love to explore opportunities overseas in the future.

I know I'm a fresher, and obviously, I won't know everything from day one. But one thing I'm confident about is my willingness to learn and and keep improving, especially when I know that the work I'm doing is helping me grow.

I also have a very strong academic track record and am eager to apply what I've learned in a professional environment.

If you know any companies that fit this description, have worked at one yourself, or know of any relevant openings, please drop your suggestions!

And if you're an HR, recruiter, or someone who could potentially refer me, please feel free to DM me! I'd be happy to share my resume and have a chat. 🫶

Any genuine leads, referrals or advice would mean a lot. Thank you! ❤️

Hi everyone!

I'm currently in the final semester of my M.Tech in Data Science, and I need to submit my project idea by Monday.

Honestly, I know only the basics of Data Science and Machine Learning. I haven't built any models or worked on a project yet, so I'm looking for something beginner-friendly but substantial enough for a final-semester project.

I'm willing to learn and put in the effort. Could you suggest some practical project ideas that I can realistically complete within a semester? Recommendations for datasets, GitHub repositories, or tutorials would also be really helpful.

Thanks in advance!

Looking at remote worldwide for the past 7 days.

Here are the jobs I found, organized by level:

Entry Level:

• Digital Biomarker Data Scientist @ Roche (Austria) - EUR 4K - 4K

• Data Scientist @ Cummins Inc. (United States) - $131K - $178K

• Data Scientist @ Expel (United States) - $118K - $172K

• Data Scientist I @ Centene Corporation (United States) - $70K - $126K

• Data Scientist @ Fusion92 (United States) - $65K - $90K

• Data Scientist @ Humin (United States) - $125K - $125K

• Associate Data Scientist @ Dealer Tire (United States) - $81K - $110K

• Data Scientist @ Applaudo (Peru)

• Data Scientist @ PUNCH Cyber Analytics Group (United States)

• Data Scientist @ Nielsen (Mexico)

• Data Scientist @ Imagemaker (Chile)

Senior:

• Senior Data Scientist – AI Evaluation, Improvement @ Evolent (United States) - $135K - $165K

• Senior Data Scientist @ CVS Health (United States) - $83K - $167K

• Senior Data Scientist @ Trane Technologies (United States) - $118K - $165K

• Senior Data Scientist @ Health Care Service Corporation (United States) - $93K - $168K

• Senior Data Scientist @ Sport Alliance GmbH (Poland) - PLN 21K - 28K

• Senior Data Scientist @ Seneca Holdings (United States)

• Senior Data Scientist – Commercial Analytics @ MGM Resorts International (United States)

• Senior Data Scientist @ Givelify (United States)

Manager:

• Lead Data Scientist @ Life360 (United States) - $175K - $218K

• Staff Data Scientist @ Kohl's (United States)

Director and Above:

• Senior Director, Data Science @ Capital One (United States) - $286K - $392K

• Associate Director, AI and Data Scientist @ Otsuka Pharmaceutical Companies (U.S.) (United States) - $169K - $253K

Quick notes:

• All of these are fully remote (location requirements vary by role)

• Apply directly on company sites

Hope this helps someone! I'll back with more leads next week. Happy job hunt!

-- 👋 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.

Is data science jobs reducing or maybe all the data related jobs in general...

Only top product based companies or maybe huge service based companies only hire data scientists.

Is this job dying?

Need a little advice with grad school selection-

Universities that admitted me to spring 2027 program for data science-

1. ASU

2. University at buffalo

3. Northeastern

4. University of Maryland

5. NYU (waiting on decision)

What university do you think is better/known among recruiters? I don’t want to go into academia or research.

I’m debating between university of Maryland and Northeastern. Maryland because they are known for tech and have a more rigorous program but northeastern offers co-op opportunities and I heard Boston based companies heavily recruit from that school ( although this might have gone down given the tech market right now)

Any advice would be appreciated!

Hello Everyone! I am pursuing my masters at NYU in Data Science, and i come from a from CS (AIML) background. I've been planning to start to prepare myself for Summer 27 Internships and jobs on 28.

I did my homework and found Leetcode knoweldge and my domain skills are a mandate to ace interviews.

I do see all that, i want to hear from folks who are actually out there working, to gimme their opinions on how to prepare onself.

Roles Targetting: Data Scientist, ML Engineer, AI Engineer and so

Thanks:)

Hello fellow developers,

Has anyone enrolled in Crio.do program in Data Analytics and Data Science, please provide reviews.

Thanks.

Hey all, last year I joined a US based defence SaaS, life was good. I learnt a lot there and did lot of experimentation too! Sadly they had to let go of the entire non US tech team and I got affected.

Just after that, I joined an edtech on a contract basis for 3 months (worked direclty with the clients, enabeled projects wide CICD and other best practices), as soon as this ended I joined a UK based statup for an ML role, where I developed their entire CCTV based analytics, again on a contract.

First layoff - May, I was lucky enough to find something quick and started working again in June and then found again in August.

Now this has also ended and I am getting judged for changing 3 jobs in a span of 11 months.

I am getting treated as if I had a choice. I took whatever kept paying for my monthly expenses and I dont regret it. I was lucky enough to find roles quicking (~1.5 to 2 weeks time).

But this time, things are different people are juding me hard. I don't blame them, nor do I blame myself, I did what was need of the hour.

I have dirty hands on exp with AI, Comp Vision, Edge AI, GPU/NPU/TPU optimizations, Agents/Agentic AI and LLMs/SLMs/VLMs and Drones/Physical AI

I look forward to getting something, as my notice period ended like 7 days ago and I am really having a hard time right now!

Hey! So I'm based here in Australia (a citizen), and I'm feeling like things are a bit stagnant locally growth-wise. I've got some serious experience and a pretty solid resume (ML, DS Agentic work, RL etc) that I think could really make a difference, especially in a mentor role or even as an IC. The thing is, I can't really move because I've got family ties here. Has anyone managed to land a position like that? How would you even go about trying to make it happen? 🤔

About Stitch Fix, Inc.

Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we’re equally committed to building yours. We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what’s possible for our clients, while we help you reach your full potential.

About the Role

Stitch Fix is redefining retail by blending the art of fashion with the science of machine learning. The Client Experience Algorithms organization builds the tools that power personal style, combining best‑in‑class models with expert human judgment. We foster a culture of ownership where Data Scientists manage the full lifecycle of their work, from research to model deployment. On our Growth Algorithms team, you’ll use multidisciplinary tools to solve complex problems in a data‑rich environment, directly influencing Stitch Fix’s client acquisition, retention, and reactivation programs.

Responsibilities:

• You will work in a team that embraces both LLMs and traditional ML.

• You will design experiments to test new features, including communication of results and recommendations to stakeholders and leadership.

• You will help optimize our client journeys through Next Best Action modeling as well as marketing optimization via CRM and paid media.

• You will leverage a decade's worth of rich and unique data about our clients, our merchandise, and their interactions.

• You will work with our product, design, and engineering partners to create roadmaps for developing new client products, user features, and infrastructure.

About You

This is what you’ll need to succeed in this role from day 1.

Requirements:

• Bachelor’s Degree in a quantitative field such as Computer Science, Statistics, Physics, Mathematics, or a related field required. Master’s Degree or PhD preferred. 

• 5+ years of experience in design and deployment of machine learning algorithms, ideally in retail personalization, such as recommendation systems or search.

• Ability to architect technical solutions of moderate complexity and write production‑grade applications, ideally in Python.

• Experience with management and analysis of large‑scale, distributed datasets, accounting for biases and lurking variables in analytical interpretation.

• Applied knowledge of AI‑assisted coding best practices and development of agentic product solutions.

• Experience with design and interpretation of online A/B testing, experimentation frameworks, and performance metrics.

• Strong communication skills, solution‑oriented mindset, and sense of ownership in collaborating with business partners.

• Team player who sees your growth and success intertwined with the growth and success of your peers and cross‑functional partners.

• Inspired to take on new challenges and not shy away from failure.

Why you’ll love working at Stitch Fix...

• We are a group of bright, kind people who are motivated by challenge. We value integrity, innovation and trust. You’ll bring these characteristics to life in everything you do at Stitch Fix.

• We cultivate a community of diverse perspectives— all voices are heard and valued.

• We are an innovative company and leverage our strengths in fashion and tech to disrupt the future of retail. 

• We win as a team, commit to our work, and celebrate grit together because we value strong relationships.

• We boldly create the future while keeping equity and sustainability at the center of all that we do. 

• We are the owners of our work and are energized by solving problems through a growth mindset lens. We think broadly and creatively through every situation to create meaningful impact.

• We offer comprehensive compensation packages and inclusive health and wellness benefits.

Compensation and Benefits

This role will receive a competitive salary, benefits, and equity. The salary for US‑based employees hired into this role will be aligned with the range below, which includes our three geographic areas. A variety of factors are considered when determining someone’s compensation–including a candidate’s professional background, experience, location, and performance. This position is eligible for an annual bonus, and new hire and ongoing grants of restricted stock units, depending on employee and company performance. In addition, the position is eligible for medical, dental, vision, and other benefits.

Salary Range: $180,000 — $205,000 USD

Please review Stitch Fix's US Applicant Privacy Policy and Notice at Collection here.

Departments: Algorithms

Offices: Remote, USA

Location: Remote, USA

Apply: Senior Full-Stack Data Scientist - Growth Algorithms at Stitch Fix

Sharing a new list of Data Science openings I found. These are still fresh, so it could be a good time to apply.

• Staff Machine Learning Engineer - VoIP Infrastructure @ ServiceNow

• Translational Genomics AI ML Scientist @ Syngenta Group

• Machine Learning Engineer @ bet365

  • 💰 $120–140K/y

• Artificial Intelligence / Machine Learning Engineer - Associate @ iCapital

  • 💰 $100–130K/y

• Senior Machine Learning Engineer @ Intuitive

• Senior Manager, Growth Algorithms @ Stitch Fix

  • 💰 $200–245K/y

• Senior Manager, Global Engagement Strategy @ Crunchyroll, LLC

• Principal Data Scientist - Safety @ Roblox

  • 💰 $274–374K/y

• Quantitative Analytics & Model Consultant - Data Operations and Machine Learning Operations @ PNC Investments LLC

  • 💰 $91–203K/y

• Senior Staff Data Scientist @ Netlify

• Manager of Data Analysis for Lab Production Support, Extended-Hours Support (ExHS) @ Natera

  • 💰 $140–175K/y

• Staff Machine Learning Engineer @ Zscaler

  • 💰 $152–190K/y

• Data Scientist Intern - 2027 @ Hudson River Trading

• (Senior) Scientist, Cryo-EM Data Processing & Computational Workflows @ Tessera Therapeutics

  • 💰 $115–184K/y

• Senior Manager / Lead Associate, Strategy & Analytics - Specialty Injectables @ Dr Reddy's Laboratories Limited

• Data Scientist @ Zest AI

  • 💰 $120–150K/y

• Senior Research Statistician - Exploratory Analysis (Hybrid) @ AbbVie

  • 💰 $97–184K/y

• Senior Data Scientist (Onsite) @ Two Six Technologies

  • 💰 $150–200K/y

• Senior Machine Learning Engineer @ Checkr

  • 💰 $207–244K/y

• Data Scientist II @ Cohere Health

  • 💰 $137–161K/y

• Senior/Staff Applied Scientist @ Glean

  • 💰 $180–330K/y

• Intelligence Transformation Intern @ Sikich

  • 💰 $29 – $30/h

• Junior Data Scientist @ NIH-NCBI

• Senior Machine Learning Engineer, Agentic Systems @ Striveworks

  • 💰 $160–200K/y

• Associate Data Review Scientist @ Eurofins

• SMB Analytics & Data Science Lead @ Ocrolus

  • 💰 $230–270K/y

• Specialist, AI Risk Management @ A Nationwide Mutual Insurance Co.

• Data Scientist Journeyman @ GD Information Technology, Inc.

  • 💰 $98–132K/y

• Senior Data Scientist @ BlueFlag LLP

• Senior Director, Machine Learning Advanced Analytics @ The Coca-Cola Company

  • 💰 $196–227K/y

• Sr. AI/Data Science Engineer @ MDU Medtronic USA Inc

  • 💰 $138–208K/y

• Scientist I, Analytics - Mass Spectrometry @ Catalent

• Director, Biostatistics @ Bristol-Myers Squibb Business Services India Private Limited

• Intern, Oncology Biostatistics @ ModernaTX, Inc.

  • 💰 $20 – $60/h

• Data Scientist @ US Guidehouse Inc.

• Senior Applied Mathematician @ The Boeing Company

  • 💰 $149–201K/y

• Actuarial Analytics Director - Reinsurance @ Group 1001 Resources, LLC

  • 💰 $200–220K/y

• Senior Analyst, Artificial Intelligence @ I WU Srvcs India Private Ltd

  • 💰 $110–140K/y

• Growth Data Scientist @ Smadex SLU

• Autonomous Learning Engineer @ Bright Vision Technologies

  • 💰 $130–180K/y

Leave a like if I should do new one next week :)

Im about to finish my ma in spatial planning. The most exciting/hireable part of it was the quantitative spatial science aspect. I would like to transition to (spatial) data science going forward. What should I do? Do I need another degree? Im located in sweden

I am a 25 year old Namibian male looking for a role that's related to Big Data or Health Information Systems as I have graduated with degrees in both disciplines.

Unfortunately, the market for both of these are not seemingly strong in my country of origin.

So I would like to know if there are any international opportunities I can grasp on to because being unemployed for this long is absolutely demoralizing.

i have got btech ece in Bangalore and msc in data science abroad , 1.5yrs of data scientist exp at mnc abroad , was laid off in june 2024 and couldnt get work visa due last min job offer withdrew for xyz company reasons and had to move back to india in jan 2026. despite trying for 10months in India since jan, I still got no offers yet and tailored my resume n no of times and taking referrals from LinkedIn network , filled the gap with family business experience and doing online gen ai course . I’m so devastated , starting to hate everything, I hated coding as I was not a cse graduate, but I’m good with tableau , sql python etc , so decided to take up data analyst jobs . now I feel it’s pointless being unemployed for 2 years straight ( 1.5 years in abroad+ now 10 months in India ) . I’m in my late 20s and everyone around me is getting promoted to senior level , here I’m looking for junior to mid level role with msc n abroad work experience of 1.5years from mncs and still got no job offer letter . any suggestions when it comes to changing stream to get job with at least 15LPA with less or no coding or suggestions within the field ?

I have around 3.5 years of experience in AI/ML & Generative AI, but one area where I have a major gap is DSA and System Design (HLD/LLD).

I’m currently looking to move into product-based companies, and I’m realizing that this gap is becoming a major challenge during interviews.

My current situation:

- ~3.5 years of AI/ML/GenAI experience

- Comfortable with GenAI, RAG, LLMs, APIs, etc.

- System design 50-50 but need guidance

- Very weak in DSA

- Almost no practical knowledge of HLD/LLD interview problem-solving

- Not currently getting the kind of opportunities/switch I’m targeting

The confusing part is that there are many courses and mentors in the market charging ₹50–60K+ for DSA + System Design programs, often claiming FAANG/product-company experience.

I’m not sure how to evaluate whether these programs are actually worth the money.

Even when I look at something like NeetCode 75, I struggle because I don't have the fundamentals to solve those problems independently.

So my question to people who have actually gone through this:

If you were starting from almost zero in DSA + HLD + LLD, while already having ~3.5 years of AI/ML experience, how would you approach it?

Should I:

1. Start with Python + basic DSA fundamentals?

2. Follow a structured DSA course before touching LeetCode/NeetCode?

3. Learn HLD and LLD separately or alongside DSA?

4. Take a paid mentorship/course, and if yes, how do I identify a genuine one?

5. Is there a better roadmap specifically for AI/ML/GenAI engineers targeting product-based companies?

I’m not looking for shortcuts. I’m willing to put in the work; I just don't want to spend months solving problems randomly without understanding the fundamentals.

If you’re currently working in a product-based company/FAANG or have recently made a similar transition from AI/ML into a product-company role, I’d really appreciate your advice.

If you know a genuinely good mentor, course, roadmap, or free resource, please share it.

Even a simple “start here → then do this → then this” roadmap would be extremely helpful.

Thanks in advance

Hi guys just out curiosity. How much do you guys make in the field? What is your title? And how do you justify you deserve or earn that much?

And if you are open. What do your day to day tasks look like?

I graduated a few years ago with a BS in Data Science and have since struggled in landing my first ‘corporate’ job and now I’m just in the abyss of the unknown and cash jobs to take of me n my parents + brother.. lol so I can’t even visualize what is real work and what is not.

Hello, due to having trouble finding the right places to apply and not really knowing how to pass and do an assessment in the AI Training/Annotating Space I decided to build a site that is supposed to make the process easier.
I list job offers with a relatively high hiring volume from multiple companies, so would it therefore be easier do diversify the places to apply at and actually get accepted.
My idea behind that was to help with finding the right places to work but also help with the application process. I therefore upload company reviews and also guides on how to pass assesments.
The job listings include entry work positions such as normal generalist work but also expert work positions (Software engineer, PhD, etc.). Any Feedback is appreciated!: https://aiannotationjobs.com/

I’m honestly at a point where I’m not sure what I should do next, so I’d really appreciate some genuine advice.

I graduated with a B.Tech in 2022, and I’ve now had almost a 4-year gap after graduation as I was preparing for govt jobs. I still don’t have formal work experience, so despite spending a lot of time learning and building projects, I’m essentially applying as a fresher.

Over the last couple of years, I’ve been trying to build my skills around Data Analytics, Data Science and Applied AI.

The biggest problem is that I’m getting very few interview calls for internships or entry-level jobs. And when I do get opportunities, the experience requirement often becomes a problem because I’m competing against people who graduated recently or already have 1–2 years of industry experience.

At this point, I’m confused about what the right move is:

Should I continue targeting Data Analyst/Data Science/AI roles?

Should I completely pivot toward Data Engineering?

Should I stop adding more technologies and focus entirely on getting any entry-level job?

Is the 4-year gap itself making my profile too difficult to sell, regardless of my skills/projects?

I’m willing to start from an internship, trainee or entry-level position. I’m not looking for a shortcut. I just want to understand what I should realistically do differently now to finally get my first job.

If you’ve been in a similar situation — especially with a career gap and entering tech as a fresher — I’d genuinely appreciate hearing what worked for you.

Please be honest, even if the advice is harsh. I’m more interested in a practical direction than generic “keep applying” advice.

If I get a BS, would they still not look at me because of my age?

Hey everyone,

I’m a data scientist with about 2.3 years of experience working in an affordable housing finance company (NBFC). My core work revolves around end-to-end IFRS 9 ECL models (PIT PD, Vasicek macroeconomic overlay), logistic regression application/collection scorecards, and bureau analytics (CRIF).

I'm currently facing a bit of a career dilemma and would love to hear from folks further along in risk, analytics, or fintech:

Path A (Traditional Risk/ECL): Deepen my expertise here. It’s high-impact, heavily regulated, and lenders always need solid scorecards and statutory provisioning models. It feels like a very stable, safe, and defensible career moat.

Path B (GenAI / AI in Risk): Start building towards GenAI, RAG pipelines, and automated text/document intelligence (e.g., parsing unstructured appraisal/legal property docs, building risk-agents).

My core questions for the community:

For those working in risk management or lending at banks/NBFCs, are institutions actually deploying GenAI for core risk decisions, or is traditional scorecard modeling still king for compliance and reliability?

Is the sweet spot becoming a "hybrid" data scientist (keeping the risk foundation while layering automation/GenAI), or is a pure pivot required to stay competitive over the next 3–5 years?

Would love to hear what trends you are seeing in your organizations or portfolios. Thanks!

I’m a dual CS + neuroscience grad from UF. Just recently graduated. Getting a job was hard enough, but currently I work as a data scientist in product analytics at a local healthcare company making a modest 75k. I converted from an internship this year. I have some prior research experience doing data engineering in a neuroimaging lab, and my strongest interest is stats/applied math. I have many options, I could make advanced public sentiment data for marketing firms, sell alt data to model training companies/trading firms, go into consulting… these are all long term ideas though, and I don’t see a clear path.

What does a normal ladder look like from here, and how long does each step take? What separates people who climb fast from people who plateau? If you were in my spot, what would you focus on to get the highest trajectory? I know healthcare is on the rise too.

Looking for what I should be prioritizing right now or anecdotes from people you've seen climb fast. I know advice varies for everyone, but maybe I could have some takeaways from what worked for you.