Director, Customer Intelligence (Data Science & Machine Learning)
Fanatics
Director, Customer Intelligence (Data Science & Machine Learning)
Job Description
Overview
As the Director of the Customer Intelligence (Data Science / Machine Learning 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+ years in Data Science/Applied ML (or equivalent) with 5+ years leading senior ICs and/or managers; proven delivery of ML products at scale.
- 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.
- 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).
- 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
- Cloud platform expertise (AWS preferred), containers/Kubernetes, and infrastructure-as-code.
- Advanced degree in CS/EE/Stats/Math/Econ (or equivalent applied experience).
Ready to build the future of sports betting? If you possess some of these skills but not all of them, we still encourage you to apply!
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 is listed in USD; actual salary will vary based on location. *Salary Range: $271,000 - $357,000 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!
About Us
About the Team
Launched in 2021, Fanatics Betting and Gaming is the online and retail sports betting subsidiary of Fanatics, a global digital sports platform. The Fanatics Sportsbook is available to 95% of the addressable online sports bettor market in the U.S. Fanatics Casino is currently available online in Michigan, New Jersey, Pennsylvania and West Virginia. Fanatics Betting and Gaming operates twenty-two retail sports betting locations, including the only sportsbook inside an NFL stadium at Northwest Stadium. Fanatics Betting and Gaming is headquartered in New York with offices in Denver, Leeds and Dublin.
Job Info
- Posting Date 10/08/2025, 07:29 PM
- Locations 95 Morton St, New York, NY, 10014, US (Remote)
- Job Schedule Full time
- Regular or Temporary Regular
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