About Arena Club
Arena Club is building the number one digital marketplace for collectibles. We started by reinventing the hobby with the first-ever digital card show, and we are expanding into new categories so collectors can buy, sell, grade, and showcase everything they care about in one place. Spearheaded by 5x World Series Champion Derek Jeter and serial entrepreneur Brian Lee, our fully digital marketplace is grounded in trust, transparency, and fun, featuring grading and authentication, vaulting, and digital pack openings that let collectors build and display their collections in a personalized online showroom from anywhere in the world.
About the Role
We’re seeking a Senior Data Scientist to join us as our first dedicated data science hire. In this key role, you will own our predictive modeling and advanced analytics, turning complex data points into actionable strategies. You will design, build, and deploy the algorithms and statistical frameworks that optimize user behavior, personalization, forecasting, and marketplace dynamics.
This is a unique opportunity for an autonomous, senior-level individual contributor who thrives on transforming ambiguous business problems into rigorous mathematical solutions. Operating at the intersection of product and commerce, you will partner closely with Product, Marketing, and Engineering teams to deliver the core data systems that drive our growth and platform performance.
What You’ll Do
- Establish the Foundation: Act as the founding data scientist, defining best practices for model development, experimentation frameworks, tracking metrics, and data repository structures
- Drive Strategic Impact: Partner directly with leadership and cross-functional teams to identify high-value opportunities where predictive modeling and data science can move core business metrics
- Build & Deploy Models: Design, build, and evaluate machine learning models and analytical frameworks that optimize dynamic pricing, forecasting, curation, and personalization
- Enhance Product & Discovery: Clean, explore, and analyze user behavior across our Marketplace and Arena Packs to drive data-driven feature decisions, optimize discovery algorithms, and improve recommendation systems
- Tackle Ambiguity: Translate open-ended, complex business questions into clear analytical problems with measurable success criteria and robust mathematical foundations
- Lead Experimentation: Design, execute, and interpret A/B tests and causal inference frameworks to rigorously measure the impact of new features, marketing campaigns, and core business initiatives
- Maintain Clean Workflows: Build reliable, localized data workflows, analysis pipelines, and reusable codebases using Python and modern data tooling
- Communicate Insights: Present complex technical findings, data visualizations, and strategic recommendations clearly to both technical and non-technical stakeholders across the organization
Qualifications
- Bachelor’s degree in Statistics, Economics, Computer Science, Mathematics, or a related quantitative field; advanced degree preferred
- 6+ years of professional experience in applied data science, with a proven track record of designing, shipping, and maintaining models or decision systems in a consumer-facing production environment
- Practical applied experience across multiple core data science disciplines: product analytics, recommendation systems, user behavior modeling, pricing, forecasting, or revenue/margin optimization
- Strong foundation in predictive analytics, supervised/unsupervised learning, statistical modeling (regression, classification, clustering), and causal inference (A/B testing, hypothesis testing, lift measurement, business impact interpretation)
- Expert-level proficiency in Python and the ML ecosystem (Scikit-learn, PyTorch or TensorFlow)
- Advanced SQL skills for complex data extraction, cleansing, feature engineering, and processing
- Experience tracking and managing experiments using tools like MLflow
- Comfort with experimentation and causal inference basics (A/B testing, lift measurement, business impact interpretation)
- Experience with AWS (EC2, S3, and related services) for data workflows
Preferred Qualifications
- Experience in marketplaces, retail or e-commerce, or consumer tech
- Familiarity with Snowflake and a dbt metrics layer
- Domain interest in collectibles, trading cards, or hard-asset markets
