<div><h2><strong>We’re Underdog.</strong></h2> <p>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.</p> <p>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.</p> <p>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.</p> <p>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.</p> <p>We’re Underdog. And winning as an Underdog is just more fun.</p> <p>Join us.</p></div><p>Were looking for a <strong>Staff Data Scientist</strong> to lead the development of personalization systems and machine learning models that enhance our product and drive measurable impact for our users. This is a high-visibility role where you’ll act as a technical leader and hands-on builder, spearheading end-to-end personalization initiatives from idea to impact.</p> <h3>About the role</h3> <ul> <li>Lead end-to-end personalization initiatives across the product, from identifying high-impact opportunities to model development, deployment, and testing.</li> <li>Design and build complex machine learning models, such as recommender systems, ranking algorithms, segmentation models, and targeting solutions.</li> <li>Partner closely with Product, Engineering, Marketing, and Data teams to implement solutions that improve user engagement, retention, and conversion.</li> <li>Drive experimentation, including A/B test design, measurement, and interpretation, to validate model and product effectiveness.</li> <li>Help define the architecture and framework for scalable, repeatable personalization systems and ensure proper model monitoring, governance, and documentation.</li> <li>Set up and lead recurring cross-functional standups to align and drive forward personalization initiatives.</li> <li>Mentor and guide junior data scientists, providing thought leadership and technical direction within the Data Science team.</li> </ul> <h3>Who you are</h3> <ul> <li>Advanced degree<strong> </strong>in mathematics, statistics, engineering, computer science, or similar field.</li> <li>6+ years of industry experience in data science or machine learning, with a focus on personalization, recommendations, targeting, or user modeling.</li> <li>Proven experience designing and implementing recommendation engines, ranking algorithms, or uplift models.</li> <li>Deep expertise in statistical modeling, experimentation (A/B testing), and causal inference techniques.</li> <li>Excellent Python programming skills, with experience building and maintaining production-ready ML code.</li> <li>Strong command of SQL and comfort working with large-scale, complex datasets.</li> <li>Experience working in cloud-based environments (e.g., AWS, GCP) and familiarity with modern data/ML tools and frameworks (e.g., Airflow, dbt, MLflow, SageMaker, Vertex AI, etc.).</li> <li>Demonstrated ability to collaborate cross-functionally and translate business problems into data-driven solutions.</li> <li>Strong business acumen and communication skills: You can explain complex technical concepts to non-technical audiences.</li> </ul> <h3>Even better if you have</h3> <ul> <li>Experience with uplift modeling, multi-armed bandits, or reinforcement learning for personalization.</li> <li>Prior work in the fantasy sports, sports betting, mobile gaming, or consumer entertainment industries.</li> <li>Contributions to building ML infrastructure, pipelines, or reusable personalization frameworks.</li> <li>Familiarity with real-time recommendation systems or event-stream processing (e.g., Kafka, Flink, Kinesis).</li> </ul> <p><em><br />Our target starting base salary range for this position is between $180,000 and $210,000, plus target equity. The starting base salary will depend on a number of factors including the candidate’s skills and experience, among other things.</em></p> <h3>What we can offer you:</h3> <ul> <li>Unlimited PTO (were extremely flexible with the exception of the first few weeks before &amp; into the NFL season)</li> <li>16 weeks of fully paid parental leave</li> <li>A $500 home office allowance</li> <li>A connected virtual first culture with a highly engaged distributed workforce</li> <li>5% 401k match, FSA, company paid health, dental, vision plan options for employees and dependents</li> </ul> <p>#LI-REMOTE</p><div><h4><strong><em>This position may require sports betting licensure based on certain state regulations.</em></strong></h4> <p><em>Underdog is an equal opportunity employer and doesnt discriminate on the basis of creed, race, sexual orientation, gender, age, disability status, or any other defining characteristic.</em></p></div>

Underdog Fantasy

Staff Data Scientist

Underdog Fantasy