Data Scientist

Summary

Join PENN Entertainment's digital team as a Senior Data Scientist and contribute to the development of cutting-edge online gaming and sports media products. You will be part of a team responsible for building net new end-to-end sports data products. The role involves machine learning, statistical modeling, A/B testing, and predictive analytics to improve theScore Bet, ESPN Bet, and iCasino products. You will collaborate with data and infrastructure engineers, and communicate with technical and non-technical stakeholders. PENN Entertainment offers competitive compensation, education reimbursements, and opportunities for career progression.

Requirements

• Have 4+ years of experience working as a Data Scientist
• Have experience solving quantitative problems with MLB Sports modelling data
• Possess a firm grasp of utilizing sport-specific problem-solving techniques to model various elements of the game
• Have the ability to dynamically project various aspects of player and team performance
• Be proficient in developing simulations replicating the dynamics and intricacies of a sporting game
• Be proficient at writing code in Python and SQL to create meaningful insights
• Have experience creating algorithms, features, and applying machine learning data models to solve sports problems
• Be able to collaboratively iterate on data science products in an experimental fashion to rapidly adapt and improve products
• Have an understanding of classification, regression and forecasting models, and A/B testing
• Have experience provisioning services using GitHub
• Have the ability to take ownership of your work to achieve the necessary high-level objectives

Responsibilities

• Develop machine learning & statistical models to predict the likelihood or expected outcome of various events across different sports
• Conduct A/B testing to inform the development of products and features
• Perform predictive & prescriptive analytics to provide in-depth knowledge on how features are working and forecasts are performing
• Develop pipelines and models, working closely with data and infrastructure engineers to deploy models and develop required data pipelines to build data products
• Develop best practices for internal data processes, including model building, modeling techniques, improved latency, and readability
• Design and build new predictive models and optimization routines with enterprise-level impact, varying from modeling expected sporting outcomes at an event level to utilizing various game state data to simulate full spectrums of expected outcomes
• Collaborate with other members of the Data Science and Engineering teams on ways to approach problems, augment code, and share new techniques
• Deploy modeling deliverables in conjunction with functional team leaders and stakeholders (in Product, Trading, etc.)
• Analyze results using solid statistical methods to iteratively improve data products
• Communicate clearly, efficiently, and empathetically with technical and non-technical stakeholders
• Write and maintain technical design and git/confluence documentation
• Perform other duties as required

Preferred Qualifications

• Have familiarity with MLFlow
• Have familiarity with AWS/GCP
• Have experience setting up ML CI/CD pipelines, testing and validating code/data, managing databases, and deploying models
• Have experience with any of Docker, Kubernetes with Terraform, Cloudwatch

Benefits

• Competitive compensation package
• Education and conference reimbursements
• Opportunities for career progression and mentoring others