Senior 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, predictive and prescriptive analytics, and developing data pipelines. You will collaborate with other data scientists and engineers to improve data products and communicate findings to stakeholders. PENN Entertainment offers a competitive compensation package, education and conference reimbursements, parental leave top-up, and opportunities for career progression.

Requirements

• 4+ Years of experience working as a Data Scientist
• Experience solving quantitative problems with MLB, NBA or NFL data
• A firm grasp of utilizing sport-specific problem-solving techniques to model various elements of the game
• The ability to dynamically project various aspects of player and team performance
• Proficiency in developing simulations replicating the dynamics and intricacies of a sporting game
• Proficient at writing code in Python and SQL to create meaningful insights
• Experienced at creating algorithms, features, and applying machine learning data models to solve sports problems
• Collaboratively iterative on data science products in an experimental fashion to rapidly adapt and improve products
• Understanding of classification, regression and forecasting models, and A/B testing
• Experience provisioning services using GitHub
• Ability to take ownership of your work to achieve the necessary high-level objectives

Responsibilities

• Machine learning & statistical modeling: predict the likelihood or expected outcome of various events across different sports
• AB Testing: use data to inform the development of products and features
• Predictive & Prescriptive Analytics: share in-depth knowledge on how features are working and forecasts are performing
• Develop pipelines and develop models: work 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 that have an enterprise level impact. This varies 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
• Other duties as required

Preferred Qualifications

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

Benefits

• Competitive compensation package
• Education and conference reimbursements
• Parental leave top up
• Opportunities for career progression and mentoring others