Senior Data Insights Specialist

3 weeks ago


Philadelphia, Pennsylvania, United States Penn Interactive Full time

Company Overview

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  • Penn Interactive is a leading interactive gaming company headquartered in Philadelphia, serving as the digital arm of PENN Entertainment, the largest regional casino operator in the U.S.
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About the Role

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  • We're seeking a skilled Data Scientist specializing in Personalization to join our Analytics & Data Science team at Penn Interactive.
  • You'll play a key role in designing and implementing innovative personalization strategies that drive significant impact on user engagement and satisfaction.
  • Your expertise will help us deliver high-quality and sustainable data-driven solutions that improve profitability, growth, and the user experience for ESPN Bet.
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Job Responsibilities

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  • Serve as a technical leader within the team, fostering a collaborative and innovative environment
  • Partner with stakeholders to deeply identify business problems that can be solved through impactful personalization initiatives
  • Utilize your mastery of recommender systems, two-tower models, and other advanced personalization techniques to architect, build, and deploy high-impact solutions that strategically advance the ESPN Bet and theScore product strategies
  • Take full ownership of critical components within data science projects, defining the roadmap and leading cross-functional teams
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Required Skills and Qualifications

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  • Ideal candidate possesses strong modeling and technical skills, a passion for rigorous statistical analysis, a background in developing and deploying high-impact personalization engines
  • University degree in Computer Science, Mathematics, Statistics or related field
  • 7+ years of industry experience (Data Scientist, ML Engineer, Tech Lead, etc.)
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Salary and Benefits

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  • $150,000 - $180,000 per year
  • A comprehensive benefits package, including medical, dental, and vision insurance, 401(k) matching, and paid time off
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About You

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  • Ideally 7+ years of industry experience (Data Scientist, ML Engineer, Tech Lead, etc.)
  • University degree in Computer Science, Mathematics, Statistics or related field
  • Familiarity with robust software engineering principles, machine learning lifecycle, and data engineering practices around creation of data pipelines, processing data, and storing data using technologies such as Spark


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