Director, Customer Intelligence (Data Science & Machine Learning)

OVERVIEW

As the Director of the Customer Intelligence DS/ML Platform team, you’ll lead a combined DS/ML group that builds, deploys, and operates production ML centered around deploying Customer Intelligence across multiple domains within Fanatics Betting & Gaming. You’ll set the multi-year strategy for applied science and platform capabilities, foster a culture of psychological safety and continuous learning, and drive measurable business outcomes through experimentation, rigorous analytics, and reliable, cost-efficient ML systems. As the leader of a growing cross-functional team, you will have significant room to explore and influence the future trajectory of numerous FBG and cross-Fanatics initiatives and peer teams, where effective Customer Intelligence applied through the right mechanisms, has the potential to be a game-changing competitive differentiator to supercharge FBG product offerings that delight and engage our fans, optimize marketing effectiveness, and bolster core unit economics for the business.

Responsibilities

• Own strategy & portfolio. Define multiyear DS/ML strategy and prioritize a cross-team roadmap supporting a range of projects across personalization, marketing, and trading/risk. Communicate clear goals and success metrics to executives and partners.
• Lead and set standards. Build and scale a high-performing small-but-mighty team of cross-functional experts. Establish succession plans, standards of excellence, and a feedback-rich, inclusive culture; set the bar for hiring, performance, and career development.
• Deliver production ML. Ship reliable real-time and batch models (feature stores, offline/online training, CI/CD for ML, model registry, canary/shadow deploys, rollback). Establish model governance, documentation, and observability (data drift, bias/fairness, performance SLOs).
• Operational excellence. Stand up on-call practices, incident response, post-mortems, and SLOs for data and model services. Drive cost efficiency (rightsizing compute, caching, autoscaling) while protecting customer experience.
• Experimentation & causal inference. Scale an experimentation program (A/B, multi-armed bandits, CUPED/causal methods) with clear guardrails, review, and instrumentation to attribute impact through causal inference techniques.
• Blend scientific and technical vision. Set credible and inspiring long-term research and scientific direction for data scientists, while maintaining the connection “from research lab to factory floor” between science and engineering.
• Stakeholder leadership. Align with Product, Risk/Trading, Marketing, and Compliance; present strategy, risks, and results to execs in clear narratives and dashboards.

Skills & Qualifications

Basic

• 10 or more years in Data Science/Applied ML (or equivalent) with 5 or more years leading senior ICs and/or managers; proven delivery of ML products at scale.
• Cross-functional leadership of ML, data, and software engineering, in close partnership with technical and business teams across an organization’s internal DS/ML ecosystem
• Expertise across predictive modeling, ranking/recommendation, and/or time-series/forecasting
• Excellence in written and verbal communication; capable of driving cross-org decisions with clear narratives and data.
• Experience launching/kickstarting 0-to-1 solutions, esp. dealing with high ambiguity and being a proactive change agent in face of decision deadlocks or unclear next-steps
• Strong product sense and business judgment

Preferred

• Experience in regulated industries (fintech/gaming) and real-time decisioning at scale.
• Experience deploying econometric and/or causal inference techniques at scale through software and systems (going beyond just analytics and reporting)
• Experience building a high-performing blended cross-functional team of scientists and engineers, working together as one team with shared goals and incentives
• Hands-on depth with Python, SQL/PySpark, ML frameworks (scikit-learn/XGBoost/TensorFlow/PyTorch), and MLOps (feature stores, MLflow/model registry, CI/CD, online serving).
• Cloud platform expertise (AWS preferred), containers/Kubernetes, and infrastructure-as-code.
• Advanced degree in CS/EE/Stats/Math/Econ (or equivalent applied experience).

The expected salary range for this role is based on job-related knowledge, skills, and experience. This role is eligible for the Fanatics Betting and Gaming annual bonus program and an equity award. *Salary Range: $201,400 - $300,000 per year (actual salary will be determined in part by a successful candidate’s geographic location). In addition to base salary, bonus, and equity, full-time employees are eligible for Medical, Dental, Vision, 401K, paid time off, and other benefits like GymPass, Pet Insurance, Family Care Benefits, and more. We’ll also give you $700 to set up your home office! Please note that visa sponsorship is not available for this position.