Underdog Sports
Senior Data Scientist
Job Summary
The role involves working within a Data Science team to develop and implement personalization models, including recommendation systems and targeting algorithms, to enhance user experience and retention. Candidates should have strong technical skills in Python, SQL, and statistics, with experience in machine learning and experimentation. The position requires collaboration across Product, Engineering, Marketing, and Data Engineering to deploy models into production. It offers flexible benefits such as unlimited PTO, parental leave, and health plans.
Required Skills
Benefits
Job Description
We’re Underdog.
The fastest-growing sports gaming company, ever. We’re here to make sports more fun. We pair intuitive user experiences with innovative game designs to build the best experience for sports fans in America.
Since 2020, we’ve launched four of today’s most widely played fantasy games, and built the Underdog Sportsbook entirely in-house with our own tech. We move fast, act with urgency, and create experiences you won’t find anywhere else.
With a $1.2 billion valuation and backing from investors like BlackRock, Spark Capital, SV Angel, Mark Cuban, Kevin Durant, Adam Schefter, and more, we’re just getting started.
At Underdog, we play and win as a team. We take chances and are unafraid to attack hard problems. We face challenges with ambition and optimism. We play for the love of the game.
We’re Underdog. And winning as an Underdog is just more fun.
Join us.
We’re looking for a Data Scientist/Senior DS to join our growing Data Science team and support the development of personalization models and infrastructure. This role is ideal for a highly curious, analytical thinker with strong technical foundations who’s excited to work on impactful projects from day one.
About the role
- Collaborate with other data scientists to build and iterate on models for personalized recommendations, targeting, and user segmentation.
- Lead personalization initiatives that span modeling, experimentation, and implementation to improve user experience and retention.
- Build and deploy machine learning models such as recommendation systems, targeting algorithms, segmentation, and ranking models.
- Design and analyze A/B tests and other experiments to evaluate the effectiveness of personalization strategies.
- Collaborate closely with Product, Engineering, Marketing, and Data Engineering to bring personalization models into production.
- Develop clean, maintainable code and contribute to reusable pipelines, feature stores, and evaluation frameworks.
- Translate data insights into compelling stories and actionable strategies for technical and non-technical audiences.
Who you are
- A degree in Math, Physics, Statistics, Economics, Computer Science, or a similar domain. MS degree preferred
- 2+ years of experience in data science, machine learning, or a related technical role.
- Hands-on experience with recommendation engines, targeting systems, ranking models, or personalization algorithms.
- Strong proficiency in Python for modeling and data manipulation.
- Advanced SQL skills and experience querying large, complex datasets.
- Solid foundation in statistics, hypothesis testing, and experimental design.
- Familiarity with cloud-based tools and platforms (e.g., AWS, GCP, Snowflake, dbt, Airflow).
- Proven ability to partner cross-functionally and influence product decisions with data.
Even better if you have
- Experience with uplift modeling, multi-armed bandits, or causal inference.
- Prior work in industries such as fantasy sports, sports betting, mobile gaming, or other B2C tech companies.
- Exposure to real-time personalization pipelines or recommender systems at scale.
- Familiarity with tools like MLflow, SageMaker, or Feature Stores.
Our target starting base salary range for this position is between $150,000 and $170,000, plus target equity. The starting base salary will depend on a number of factors including the candidate’s skills and experience, among other things.
What we can offer you:
- Unlimited PTO (we're extremely flexible with the exception of the first few weeks before & into the NFL season)
- 16 weeks of fully paid parental leave
- A $500 home office allowance
- A connected virtual first culture with a highly engaged distributed workforce
- 5% 401k match, FSA, company paid health, dental, vision plan options for employees and dependents
#LI-REMOTE
This position may require sports betting licensure based on certain state regulations.
Underdog is an equal opportunity employer and doesn't discriminate on the basis of creed, race, sexual orientation, gender, age, disability status, or any other defining characteristic.
Underdog Sports
A fantasy sports platform offering daily contests and games for sports enthusiasts to compete and win prizes.
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