Director of Data Science
fanaticscollectibles
This is a leadership role in machine learning and data science at a company operating at real scale. Fanatics runs a global platform serving over 100 million sports fans across commerce, collectibles, and betting. As a Director, you'd own data strategy and ML systems that power decisions across the entire business—not just analyze dashboards, but shape how the platform works.
You'll build and lead teams working on recommendation systems, user behavior modeling, fraud detection, and other core problems. You'll work cross-functional with product, engineering, and business teams to turn data into strategy. The role is based in New York and is not remote.
This fits people with strong ML fundamentals, experience building systems (not just notebooks), and the ability to communicate technical work to non-technical stakeholders. You should be comfortable with Python, SQL, and statistical thinking. A portfolio or prior projects showing end-to-end work is better than credentials alone.
To apply, submit your resume and a brief note on why this role interests you through CareerJumpShip. Include links to your work if you have them—GitHub, papers, or past projects.
About this role
About Us Fanatics is building a leading global digital sports platform. We ignite the passions of global sports fans and maximize the presence and reach for our hundreds of sports partners globally by offering products and services across Fanatics Commerce, Fanatics Collectibles, and Fanatics Betting & Gaming, allowing sports fans to Buy, Collect, and Bet. Through the Fanatics platform, sports fans can buy licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods; collect physical and digital trading cards, sports memorabilia, and other digital assets; and bet as the company builds its Sportsbook and iGaming platform. Fanatics has an established database of over 100 million global sports fans; a global partner network with approximately 900 sports properties, including major national and international professional sports leagues, players associations, teams, colleges, college conferences and retail partners, 2,500 athletes and celebrities, and 200 exclusive athletes; and over 2,000 retail locations, including its Lids retail stores. Our more than 22,000 employees are committed to relentlessly enhancing the fan experience and delighting sports fans globally. Collaborate with cross-functional partners in operations, finance, marketing, and engineering to understand business imperatives and scope data science projects; Explore possibilities to solve the business imperatives by identifying data sources, creating data where needed, and applying data science techniques; Work with VP Data, VP of Analytics, and CFO to create data-informed business strategies and roadmaps; Translate data needs into data product requirements, evaluate technologies, and identify opportunities to innovate and improve data science capabilities; Use creative problem-solving skills to analyze data and build statistical / machine learning models to help solve business problems from different perspectives; Work with data engineering lead to create services that can ingest and supply data to and from both internal and external sources and ensure data quality and timeliness; Build the data science team and lead in data scientist recruitment process; Guide and coach data scientists and own the deliverables of data visualization and dashboards to help the organization monitor performance, generate insights, and continuously improve user experience; Continuously grow the data science team’s skillsets; Establish playbooks to drive data product development process and consistent outcomes; Use strong communication skills (written and verbal) to lead the full lifecycle of model development, which spans from business problem discovery, data discovery to model deployment and monitoring; Evangelize data science across the entire company; identify and make the business case for data science based use cases; Where needed, conduct hands-on wrangling, processing, cleansing, and verifying data from different sources used for analysis; Analyze data with complex relationships, hierarchical levels, and time series, such as Pandas, PySpark; Use and recommend a wide range of machine learning algorithms and statistical modeling, including latest LLM developments; Utilize data visualization and dashboard tools, such as Tableau, PowerBI and Snowflake. Up to 10% domestic travel required for meetings/clients visits; 100% remote; must reside in U.S.; reports to HQ in New York, NY. Salary: $336,350 - $356,350 per year. MINIMUM REQUIREMENTS: Bachelor’s Degree or U.S. equivalent in Quantitative Methods, Statistics, Econometrics, or related field, plus 5 years of professional experience as a Data Scientist, Operations Research Analyst, or any occupation, job title, or position leading a data science team in a technology organization. Must also have experience in the following: 5 years of professional experience implementing data science solutions by identifying relevant data sources, creating data pipelines, and applying advanced data science techniques to support business decision-making; 5 years of professional experience designing and developing machine learning models and statistical algorithms to analyze structured and unstructured data from both internal and external sources; 5 years of professional experience collaborating with cross-functional teams to gather business requirements, define technical scopes, and deliver actionable data insights; 5 years of professional experience utilizing tools and libraries including Python, SQL, Spark, PyTorch, Pandas, and PySpark to perform data wrangling, cleansing, and advanced analytics; 5 years of professional experience developing and maintaining data visualization dashboards using tools including Tableau to monitor performance and communicate insights to stakeholders; 5 years of professional experience establishing scalable data product development processes through consistent use of playbooks, code standards, and reproducible pipelines; 5 years of professional experience leading the full lifecycle of machine learning models from business problem discovery to model deployment and performance monitoring; 5 years of professional experience evangelizing data science practices across organizations, including coaching team members, supporting recruitment efforts, and promoting a data driven culture. CONTACT: Apply online at fanaticsinc.com/careers or email resume to: WorkWithFanatics@FanaticsInc.com. Must specify Ad Code ZCKM in subject line. #LI-DNI #LI-DNP By submitting your application, you agree to our terms of service and acknowledge you have read our Candidate Privacy Policy.
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