Staff Data Scientist

1 Week ago • 7 Years + • Data Analyst

About the job

Summary

As a Staff Data Scientist specializing in Personalization at Penn Interactive, you will design and implement innovative personalization strategies for ESPN Bet. Responsibilities include partnering with stakeholders, leveraging recommender systems and two-tower models, owning critical project components, collaborating with engineers, and presenting solutions to leadership. You will drive user engagement and satisfaction through data-driven solutions, ensuring seamless integration and deployment of personalization engines. The role requires expertise in machine learning, data science principles, and strong communication skills.
Must have:
  • 7+ years of experience
  • Expertise in personalization engines
  • Strong Python coding skills
  • Machine learning lifecycle knowledge
  • Data engineering understanding
  • Excellent communication skills
Good to have:
  • Sports betting industry knowledge
  • Experience with Airflow, Dagster, or DBT
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Penn Interactive (PI) is an interactive gaming company headquartered in Philadelphia. PI is the digital arm of PENN Entertainment (NASDAQ: PENN), the largest regional casino operator in the U.S.). Our mission is to challenge the norms of the gaming industry by building an immersive interactive gaming experience that is responsible, innovative, and fun. We are committed to helping our team members grow and succeed.  We believe that hiring talented individuals that love what they do will help us win!

About the Role & Team 
On the Analytics & Data Science, our mission is to develop high-quality and sustainable data-driven solutions that improve profitability, growth, and the user experience for ESPN Bet.  As a Staff Data Scientist specializing in Personalization, you'll play a key role in designing and implementing innovative personalization strategies that drive significant impact on user engagement and satisfaction. You'll leverage your deep understanding of data science principles, techniques, and tools, as well as your proven expertise in personalization engines, to design, build, and deploy sophisticated models that deliver the right content, to the right user, at the right time. 

The ideal candidate possesses strong modeling and technical skills, a passion for rigorous statistical analysis, a background in developing and deploying high-impact personalization engines, and a genuine interest in the world of professional sports, betting, and esports. 

About the Work 

  • 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
  • Collaborate with Data Engineers and Machine Learning Engineers to guarantee seamless integration, deployment, and production readiness
  • Contribute to the ongoing evolution of our data science infrastructure and champion best practices
  • Drive Innovation by staying at the forefront of data science and machine learning trends
  • Confidently present your solutions and strategic recommendations to diverse audiences, including senior leadership, using compelling narratives, insightful data visualizations, and a deep understanding of business implications to influence critical decision-making
  • Other duties as required


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
  • Strong track record of designing, prototyping, scaling and deploying data science products to solve complex business challenges (with a focus on recommendation engines)
  • Expert coding skills in general purpose languages like Python, and familiarity with robust software engineering principles
  • Deep understanding of Machine Learning lifecycle, best practices, algorithms and domains
  • Fundamental understanding of the data engineering practices around creation of data pipelines, processing data and storing data using technologies such as Spark  
  • Experience collaborating with and understanding the needs of stakeholders from a variety of business domains and ability to incorporate their expertise into the end state solution  
  • Demonstrated ability to take a product-oriented mindset in using conceptual and innovative thinking to develop and apply solutions taking into consideration the user experience
  • Proven ability to communicate complex topics clearly and effectively to audiences of varying technical levels both in written and oral settings
  • Experience with automation & orchestration tools such as Airflow, Dagster, DBT or Cron jobs.
  • Knowledge of the sports betting industry is preferred, but not mandatory 

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Check out our LinkedIn page!

Recently being recognized as a top workplace in the United States, we believe people work their best when they can be themselves. We are looking for hungry, innovative thinkers to help us challenge the status quo of the gaming industry.  Diversity, equity, and inclusion are vital to all of our processes, programs, and structures. Your story, who you are, and your experience matter here.

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About The Company

Penn Interactive (PI) is an interactive gaming company headquartered in Philadelphia,PA with offices in Greenfield, MA, and Cherry Hill, NJ. As the digital arm of PENN Entertainment (NASDAQ: PENN), North America’s leading provider of integrated entertainment, sports content, and casino gaming experiences, we are poised for fast-paced growth in the sports betting and online casino space. We have teamed up with theScore to create a unique and exciting sports betting experience through our retail books and the Sportsbook mobile apps.

Pennsylvania, United States (Hybrid)

Pennsylvania, United States (On-Site)

Pennsylvania, United States (On-Site)

Pennsylvania, United States (On-Site)

Pennsylvania, United States (Hybrid)

Pennsylvania, United States (On-Site)

Pennsylvania, United States (Hybrid)

Pennsylvania, United States (Hybrid)

Pennsylvania, United States (Hybrid)

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