Applied Data Scientist

🔥 16 hours ago

🌐 Israel, United States – Remote

🇮🇱 Israel – Remote 🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 15%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Nift

WebsiteLinkedInAll Job Openings

11 - 50 employees

📣 Marketing

💼 Consulting

📦 Logistics

💰 $16.5M Series A on 2018-03

Marketing • Consulting • Logistics

Nift is a technology company that acts as a matchmaker between customers and businesses. By creating a network that connects great customers with outstanding businesses, Nift aims to help both parties thrive. The company offers gifts to potential customers, encouraging them to experience and discover new businesses they may love.

📋 Description

• 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 • 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

🎯 Requirements

• 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 • Ability to measure model success through business outcomes such as revenue, conversion, churn, or similar KPIs