Note: The job is a remote job and is open to candidates in USA. Fanatics is building a leading global digital sports platform. They are seeking a Data Scientist III to drive predictive insights through a cross-vertical enterprise lens, translating fan signals into measurable enterprise value through advanced segmentation and targeting models.

Responsibilities

• Develop a deep understanding of the end-to-end customer lifecycle across all Fanatics lines of business, building a unified view of fan behavior across commerce, betting, collectibles, and media
• Build, deploy, and iterate on Lifetime Value (LTV) models, including probabilistic frameworks and retention-based approaches, to improve enterprise customer segmentation and cross-sell opportunities
• Design and implement churn, reactivation, and propensity models that feed directly into loyalty, CRM, and promotional decision-making across business units
• Apply causal inference and uplift modeling to measure true incremental value of cross-BU promotions and personalization strategies
• Develop analytical and science frameworks that facilitate enterprise trade-offs and executive decision-making across business units
• Build strong relationships with stakeholders across Advertising & Loyalty, Betting & Gaming, and eCommerce & Collectibles to drive an ecosystem-wide data mindset

Skills

• A minimum of 3-5 years proven experience in a data science or advanced analytics role
• Degree in a quantitative field, e.g., Mathematics, Physics, Statistics, Engineering, or Computer Science, Economics
• Strong SQL proficiency and strong proficiency in Python, with experience building and validating machine learning models
• Hands-on experience with LTV or customer value modeling (probabilistic frameworks, retention curve modeling, or cohort-based CLV) in a consumer, subscription, or transactional environment
• Proven experience with experiment design in loyalty or promotional contexts
• Strong grasp of survival analysis and its application to customer churn and retention modeling
• Demonstrated ability to partner with stakeholders, earning trust through data-driven insights and clear communication
• Outcome-oriented and data-driven; comfortable navigating fast-paced, high-growth environments
• Prior experience with multi-brand or multi-product customer data, identity resolution, or unified customer modeling across verticals
• Experience experimenting with Generative AI solutions (e.g., LLM-based analysis, automation, or insight generation) and identifying opportunities to apply them within a commercial analytics environment

Company Overview

Company H1B Sponsorship