Applied Data Scientist
Nift
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2,031 open scientist roles across 269 companies are on ApplySarthi right now, most of them in Bengaluru (133), Hyderabad (72), Delhi NCR (32).
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What scientist roles keep asking for: Python (49%), Machine learning (37%), SQL (23%), C++ (18%), Java (17%), Deep learning (14%), R (14%), LLMs (13%) — counted across their open postings here.
Deep learning jobs · Machine learning jobs · PyTorch jobs · Python jobs
Nift has 13 open roles listed here.
- Partner Success Manager
- Account Executive, Mid-Market Partnerships
- ML Ops Engineer
- Sales Director, Mid-Market
- Sales/Account Executive — Performance Marketing / DTC Brands (Remote)
Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for scientist roles keep coming back to Python, Machine learning, SQL, C++. Practise those questions before you sit with Nift.
Questions you are likely to be asked
- Why do you want to join Nift?
- What is your experience with Deep learning? Tell me one thing you learned the hard way.
- When would you not use machine learning for a problem?
- Walk me through a model you built, from the data to how it was used.
- How did you know your model was actually good, and not just good on your test set?
Prep Sarthi gives you a free mock interview: an AI interviewer asks you questions like these out loud, from your own CV and this job, and shows your score and your weakest answer.
Practise the Applied Data Scientist at Nift interview free →Nift is disrupting performance marketing, delivering millions of new customers to brands every month. We're hiring a hands-on Senior Applied Data Scientist to help build and scale production-grade recommendation systems that drive our core marketplace outcomes.
This is not a research-only role. We're looking for someone who can take models from idea to production — running experiments, measuring business impact, and continuously improving the systems behind how Nift matches people with the right brands. You'll own the full lifecycle: exploratory analysis, data prep, modeling, testing, deployment, and post-launch measurement.
The ideal candidate has worked in a real production environment, brings strong deep learning experience, and understands recommendation systems in practice — not just in theory. Success here means shipping models that move Nift's core KPIs, connecting technical work to measurable business impact, and helping the team scale with strong engineering discipline.
This role is ideally based in Israel, but strong candidates in the U.S. will also be considered.
What You'll Do
- Own the full funnel of applied machine learning work, from idea through production
- Build, improve, and deploy recommendation models that support Nift's core business goals
- Tackle deep learning problems in a production setting — not just offline experimentation
- Conduct exploratory data analysis, preprocessing, feature development, and modeling
- Run experiments and evaluate success against business KPIs, not just model metrics
- Partner with engineering and infrastructure teammates to productionize models and scale systems
- Improve recommendation quality, personalization, and the business performance tied to those systems
What You'll Have
- 5+ years of experience in production data science environments
- Strong hands-on experience taking machine learning models into production
- Strong deep learning experience; proficiency with PyTorch or TensorFlow is expected
- Direct experience with recommendation systems, or adjacent experience in areas like bidding or dynamic pricing
- Strong Python and SQL skills
- Experience working with data at meaningful scale — high-scale environments are a strong plus
- The ability to measure model success through business outcomes such as revenue, conversion, churn, or similar KPIs
Bonus points for:
- A Master's degree, especially paired with strong production experience
- A PhD paired with meaningful production-grade work (purely academic backgrounds aren't the target profile for this role)
- A software engineering background — particularly for candidates who've built pipelines and production systems before moving into machine learning
About Us
Our mission is to reshape how people discover and try new brands by introducing them to new products and services through thoughtful "thank-you" gifts. Our customer-first approach ensures businesses acquire new customers efficiently while making customers feel valued and rewarded.
We are a data-driven, cash-flow-positive company that has experienced 731% growth over the last three years. Now we're scaling to become one of the largest sources of new customer acquisition worldwide. Backed by investors who supported Fitbit, Warby Parker, and Twitter, we're poised for exponential growth and ready to demonstrate impact on a global scale.
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Listed on greenhouse · posted 2026-08-03. ApplySarthi collects openings and links to application pages; the role is advertised by Nift, not by us.