New york city base pyy range: $181,477—$266,166 us...
On-site
Lead data science team
Apply mixed methods
Develop data assets, reports, insights
Epic Games is seeking a Data Science Lead for their Gameplay Analytics team in New York City. The ideal candidate will have extensive experience in data analytics, team management, and a strong background in live service video games
Job Summary
Lead a team of Data Scientists and Data Programmers applying mixed methods to own the end-to-end life cycle of creating data assets, reports, and insights.
Partner with design, game development, and product management counterparts to identify opportunities and use data to develop metrics and insights that shape strategy.
Work with design, product, and analytics teams to quickly and rigorously design, test, and learn from experiments to improve our games.
Matching Summary
Match Score: 85
Epic Games is seeking a Data Science Lead for their Gameplay Analytics team in New York City. The ideal candidate will have extensive experience in data analytics, team management, and a strong background in live service video games.
Salary
New York City Base Pay Range: $181,477—$266,166 USD
Skills & Requirements
Must-have
Lead data science team
Apply mixed methods
Develop data assets, reports, insights
Influence development and product teams
Partner with stakeholders
Develop metrics and insights
Instrument data and ensure quality
Write efficient and scalable SQL
Python analytics ecosystem development
Experimental design and A/B testing
Nice-to-have
Familiarity with distributed computing using Spark
Familiarity with operational processes
Advanced statistical training
Experience in a "full-stack" environment
Key Requirements
At least 5 years of industry or relevant experience
Proven interest in and knowledge of live service video games
At least 2 years of experience managing a team of data professionals
Strong product intuition
Experience with working with development teams
Familiarity with supporting operational processes (Github, Airflow, Claude Code)
Understanding of experimental design and A/B testing techniques