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Fanatics · 16 hours ago

Director, Customer Intelligence (Data Science & Machine Learning)

United States

Full-time

Remote

Director/Executive

$201K/yr - $300K/yr

10+ years exp

Fanatics is building a leading global digital sports platform, and they are seeking a Director of the Customer Intelligence DS/ML Platform team to lead a combined DS/ML group. This role involves setting the multi-year strategy for applied science and platform capabilities, fostering a culture of continuous learning, and driving business outcomes through experimentation and analytics.

eSportsManufacturingRetailSporting GoodsSports

No H1B

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

Qualification

Data Science/Applied MLPredictive modelingPythonCross-functional leadershipSQL/PySparkML frameworksCloud platform expertiseCausal inference techniquesProduct senseBusiness judgmentWritten communicationVerbal communication

Required

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)