Senior Data Insights Specialist
3 weeks ago
Company Overview
">- 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.
About the Role
">- 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.
Job Responsibilities
">- 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
Required Skills and Qualifications
">- 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.)
Salary and Benefits
">- $150,000 - $180,000 per year
- A comprehensive benefits package, including medical, dental, and vision insurance, 401(k) matching, and paid time off
About You
">- 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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