Senior Data Scientist
פורסם אתמול · 0 מועמדים
- 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
חולץ מתיאור המשרה · מתעדכן אוטומטית
תיאור המשרה המלא
המשרה המקורית · נשמר לעיוןA leading SportsTech company is looking for a Senior Data Scientist to join its growing team.
Our platform combines the intensity of live sports with cutting-edge technology to deliver a personalized experience to millions of users worldwide.
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
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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 system
• Proven experience deploying and monitoring real-time ML models in production
• Familiarity with experiment tracking, model versioning, and performance monitoring
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- 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