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Open nowFirst seen 2 days ago

Data Scientist

365scores/b3.0068 open roles

Where
Tel Aviv
Work mode
On site
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Your applicationOpen nowData Scientist365scores/b3.006 · Tel Aviv

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: first seen 2 days ago

The posting

At 365Scores, we're revolutionizing how fans receive and interact with live sports updates and data. Our platform combines the intensity of live sports with cutting-edge technology to deliver a personalized experience to millions of users worldwide.

As a Senior Data Scientist at 365Scores, you will be an integral part of our Machine Learning and AI team. The role is hands-on and impact-driven, focusing on building, improving, and delivering machine learning models that directly support business goals.

Responsibilities

  • Design and deploy production ML systems that drive automated business decisions (pricing, bidding, resource allocation)
  • Build end-to-end ML pipelines — from data ingestion and model training to serving, monitoring, and incident response
  • Translate ambiguous business problems into rigorous mathematical frameworks and own them from conception to production impact
  • Conduct rigorous experimentation (A/B testing, causal inference, uplift modeling) to measure and improve model performance
  • Maintain and improve real-time models that adapt to incoming data and feedback signals
  • Mentor junior team members on ML best practices and production standards

Requirements

  • 5+ years in ML roles with demonstrated production impact
  • Advanced degree (MS/PhD) in a quantitative field, or equivalent industry depth
  • Deep expertise in mathematical optimization — convex, constrained, and gradient-based methods
  • Hands-on experience with Bayesian or hyperparameter optimization
  • Strong causal inference skills — propensity scoring, uplift modeling, or experimental design
  • Applied ML experience in optimization domains: pricing, bidding, or resource allocation
  • Advanced time series modeling for dynamic, decision-making systems
  • Proven experience deploying and monitoring real-time ML models in production
  • Familiarity with experiment tracking, model versioning, and performance monitoring
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