Data Scientist, MLB Sports Modeling (Coop) - F2025
Data Scientist, MLB Sports Modeling (Coop) - F2025
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Job Description
PENN Entertainment Inc. is North Americas leading provider of integrated entertainment sports content and casino gaming experiences. From casinos and racetracks to online gaming sports betting and entertainment content we deliver the experiences people want how and where they want them.
Were always on the lookout for those who are passionate about creating and delivering cuttingedge online gaming and sports media products. Whether its through ESPN BET Hollywood Casino theScore Bet Sportsbook & Casino or theScore media app were excited to push the boundaries of whats possible. These stateoftheart platforms are powered by proprietary inhouse technology a key component of PENNs omnichannel gaming and entertainment strategy.
When you join PENN Entertainments digital team youll not only work on these cuttingedge platforms through theScore and PENN Interactive but youll also be part of a company that truly cares about your career growth. Were committed to supporting you as you expand your skills and explore new opportunities.
With locations throughout North America you can build a future at PENN Entertainment wherever you are. If you want to challenge conventions in gaming media and entertainment we want to talk to you.
Workterm: September 2 2025 December 19 2025
Number of Openings: 1
Hiring Teams:
- MLB Sports Modeling
Interview Notes:
- Technical assignment to be sent prior to interviews.
About the Team:
Our Data Science team is responsible for building models forecasts and simulations to help improve theScore Bet ESPN Bet and iCasino products. Our team values creativity collaboration ingenuity and ownership. We are looking for someone who is interested in joining a team responsible for building endtoend sports data products to further our teams mission of creating a worldclass datadriven product experience.
About the Work:
- Data Analysis:Assist in analyzing sports data to inform the development of our products and features.
- Model Building:Help build and test predictive models to forecast various sports outcomes.
- Support Pipeline Development:Work closely with data and infrastructure engineers to support data pipeline development.
- Research & Documentation:Conduct research and help maintain documentation for data science projects.
- Collaboration:Collaborate with team members to approach problems augment code and share new techniques.
- Communication:Communicate findings and insights clearly and efficiently with team members.
About You:
- Currently enrolled in a Computer Science degree Statistics Business or related field.
- Coding Skills:Moderate proficiency in Python and SQL.
- Data Skills:Able to handle data wrangling skills around JSON and tabular data.
- Analytical Skills:Strong problemsolving skills with an interest in sports data.
- Team Player:Ability to work collaboratively in a team environment.
- Eager to Learn:Enthusiastic about learning new techniques and technologies in data science.
- Nice to Have:
- Familiarity with Machine Learning:Familiarity with machine learning concepts and techniques.
- Experience with Sports Data:Any experience or coursework related to sports data analysis (specifically for MLB)
- Cloud Knowledge:Familiarity with cloud services like AWS or GCP.
- Version Control:Basic knowledge of version control systems like GitHub.
What We Offer:
- Fun relaxed work environment
- A voice. Were dedicated to open communication which empowers our employees to drive the companys culture
- A company that encourages a culture of inclusion and diversity
- Opportunity to work on large scale consumerfacing applications with millions of users
- Career growth.
- Mentorship from some of the brightest people in the industry
Candidates residing in Ontario requiring special accommodation can email
theScore iscommitted to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race color religion gender gender identity or expression sexual orientation national origin genetics disability or age.
Employment Type
Full Time
