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Applied Data Scientist

Nift Open · verified Oct 24, 2026
Remote Israel Mid-level Data Science

At a glance

Mid-level Data Science role at Nift. Remote, Israel.

Pay not stated Data Science salary

RoleData Science
SeniorityMid-level
LocationIsrael
WorkplaceRemote
PostedAug 3, 2026 · 2mo ago
Role brief

dataroles summary, based on the employer's posting.

What you'll do

  • Take applied machine learning from initial analysis and data preparation through modeling, deployment and follow-up measurement
  • Build and refine recommendation models that support marketplace goals and improve personalization
  • Run experiments and judge results by business KPIs as well as model performance
  • Work with engineering and infrastructure teammates to launch models and scale the systems behind them

What you bring

  • At least five years working in production data science environments
  • Hands-on experience putting machine learning models into production, including substantial deep learning work
  • Practical recommendation-system experience, or related work in bidding or dynamic pricing
  • Strong Python and SQL skills, plus proficiency in PyTorch or TensorFlow

Who this fits

This role suits a hands-on data scientist who wants to build and improve production recommendation systems, rather than focus only on research. You should connect model work to business results such as revenue, conversion or churn. The role is ideally based in Israel, with strong candidates in the U.S. also considered.

From the employer

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.

Opportunity

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Each morning you get everything that fits, strongest first.

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Find me work

By the team behind dataroles.

Find me work
Opportunity

Data Science work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind dataroles.