Job description

Fanatics Commerce is the global leader in licensed sports merchandise, operating a vertically integrated platform that designs, manufactures, and delivers officially licensed apparel, jerseys, headwear, and collectibles for major leagues, teams, and events worldwide. With more than 900 e-commerce sites and a global omnichannel presence across digital, in-venue, and retail, Fanatics Commerce reaches fans in over 180 countries and powers official fan experiences for many of the world's most iconic sports properties. At Fanatics, we bring our BOLD Leadership Principles to life every day - building championship teams, obsessing over fans, acting with entrepreneurial speed, and delivering with a determined and relentless mindset. As we continue to scale our global platform, the Senior Data Scientist, Supply Chain & Inventory Optimization will play a critical role in maximizing supply chain efficiency and inventory financial performance through ML-driven modeling, pricing optimization, and demand forecasting. ROLE OVERVIEW This role sits within a high-impact team responsible for product lifecycle modeling, pricing and promotional optimization, clearance management, demand forecasting, network simulation, and inventory sourcing, allocation, and balancing. The Senior Data Scientist will bring a rigorous, ML-driven mindset across operational modeling, forecasting, pricing, and product strategy — moving fluidly across domains in a collaborative, fast-moving team culture with a strong emphasis on delivering measurable business impact amid frequently shifting requirements. The Senior Data Scientist delivers business and fan impact through BOLD leadership and execution excellence, leveraging data, automation, and AI-enabled insights. HOW WILL YOU DRIVE IMPACT Success is measured by the ability to deliver results through BOLD capabilities and measurable outcomes. Team & Leadership Impact (Build Championship Teams) Partner cross-functionally with engineering, product, and operations teams to frame complex supply chain and inventory problems and translate analytical models into decisions and tools that get adopted. Communicate modeling tradeoffs and results clearly to both technical and non-technical audiences, building trust and shared understanding across teams. Contribute to a collaborative team culture by sharing methodologies, reviewing peers' work, and supporting the growth of junior data scientists. Fan & Customer Impact (Obsessed with Fans) Build demand forecasting and product performance models that ensure the right products are available to fans at the right time and place. Develop pricing and promotional optimization models that improve the fan value experience while protecting financial performance. Support clearance management strategies that minimize inventory surplus without compromising the fan-facing product assortment. Deliver decision-support tools and stakeholder-facing reporting that translate complex models into actionable insights for operations and product teams. Innovation & Problem Solving (Limitless Entrepreneurial Spirit) Design, test, and deploy time series models for demand forecasting, product lifecycle tracking, and performance analytics using both classical (ARIMA, exponential smoothing) and ML-based approaches (XGBoost, LSTM, DeepAR). Build and refine pricing, clearance, and network optimization models using discrete optimization techniques — including MIP, constraint solvers, and genetic algorithms — alongside simulation and heuristic methods. Apply exploratory data analysis and statistical methods to uncover performance drivers, engineer predictive features, and inform model design decisions. Develop scalable pipelines and automation tools using Python, Spark, and cloud infrastructure to operationalize models at scale. Ownership & Execution (Determined & Relentless Mindset) Own the full model development lifecycle — from problem framing and data engineering through training, evaluation, deployment, and monitoring — across supply chain and inventory initiatives. Develop and maintain predictive models spanning forecasting, classification, regression, clustering, and segmentation in a production or operational environment. Deliver consistently against business objectives in a fast-paced environment with frequently shifting priorities and requirements. Take accountability for the measurable business impact of deployed models, tracking outcomes and iterating based on real-world performance. AI & DIGITAL CAPABILITY We are building a future-ready organization. This role is expected to: Apply AI and technology to improve efficiency, quality, and outcomes Use data and digital tools to inform decisions and enhance performance Demonstrate curiosity and adaptability in adopting new technologies and ways of working Contribute to a culture of innovation and continuous improvement CAPABILITIES & EXPERIENCE YOU BRING Required Qualifications: 6+ years of experience building and deploying predictive models — spanning supervised learning (regression, classification), unsupervised learning (clustering, dimensionality reduction), and time series forecasting — in a production or operational environment. Strong proficiency in Python (Pandas, Scikit-learn, NumPy) and SQL, with hands-on experience using Spark or another distributed computing framework for scalable data processing. Deep expertise in time series forecasting using both classical methods (ARIMA, exponential smoothing) and ML-based approaches (XGBoost, LSTM, DeepAR), including rigorous model evaluation practices. Demonstrated experience applying discrete optimization techniques — including mixed-integer programming, constraint solvers, and genetic algorithms — to real-world business problems such as pricing, clearance, or network design. Familiarity with simulation-based modeling and tradeoff analysis for operational or supply chain decision-making. Experience with feature engineering and EDA-driven insight development to inform model design and uncover business performance drivers. Strong communication skills with the ability to clearly explain modeling tradeoffs and results to both technical and non-technical stakeholders. Nice to Have: Experience with data visualization and BI tools such as Superset or Tableau for stakeholder-facing reporting. Prior experience in retail, e-commerce, or supply chain domains. Experience mentoring or guiding junior data scientists. Education: Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Operations Research, or a related field. Where you’ll work and what’s required Location: Redwood City, CA Office Hybrid work environment flexibility, with Tuesdays, Wednesdays, and Thursdays in office; Mondays and Fridays remote. Ability to travel up to 10% of the time for partner meetings, events, and other related activities. The salary range represents base pay only and does not include short-term or long-term incentive compensation. When determining base pay as part of a final compensation package, we consider several factors such as location, experience, qualifications, and training. For information about our benefits, please visit benefitsatfanatics.com Salary Range $170,000 — $210,000 USD At Fanatics, we operate with a BOLD mindset - We Build Championship Teams, we’re Obsessed with Fans, we embrace a Limitless Entrepreneurial Spirit, and we approach every challenge with a Determined and Relentless Mindset. If you’re ready to contribute to a dynamic, fast-paced environment that thrives on collaboration and growth, we want you to be part of our team. 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. ABOUT THE TEAM Fanatics Commerce is a leading designer, manufacturer, and seller of licensed fan gear, jerseys, lifestyle and streetwear products, headwear, and hardgoods. It operates a vertically-integrated platform of digital and physical capabilities for leading sports leagues, teams, colleges, and associations globally – as well as its flagship site, www.fanatics.com . Fanatics Commerce has a broad range of online, sports venue, and vertical apparel partnerships worldwide, including comprehensive partnerships with leading leagues, teams, colleges, and sports organizations across the world—including the NFL, NBA, MLB, NHL, MLS, Formula 1, and Australian Football League (AFL); the Dallas Cowboys, Golden State Warriors, Paris Saint-Germain, Chelsea FC, and Tokyo Giants; the University of Notre Dame, University of Alabama, and University of Texas; the International Olympic Committee (IOC), England Rugby, and the Union of European Football Associations (UEFA). At Fanatics Commerce, we infuse our BOLD Leadership Principles in everything we do: · Build Championship Teams · Obsessed with Fans · Limitless Entrepreneurial Spirit · Determined and Relentless Mindset By submitting your application, you agree to our terms of service and acknowledge you have read our Candidate Privacy Policy. Fanatics will never ask candidates for money, banking information, or other sensitive personal information as part of the interview process. If you receive a suspicious message claiming to be from Fanatics recruiting, please do not respond and report it here .

Requirements

Must-haves

Success is measured by the ability to deliver results through BOLD capabilities and measurable outcomes.
Team & Leadership Impact (Build Championship Teams)
Partner cross-functionally with engineering, product, and operations teams to frame complex supply chain and inventory problems and translate analytical models into decisions and tools that get adopted.
Communicate modeling tradeoffs and results clearly to both technical and non-technical audiences, building trust and shared understanding across teams.
Contribute to a collaborative team culture by sharing methodologies, reviewing peers' work, and supporting the growth of junior data scientists.
Fan & Customer Impact (Obsessed with Fans)
Build demand forecasting and product performance models that ensure the right products are available to fans at the right time and place.
Develop pricing and promotional optimization models that improve the fan value experience while protecting financial performance.
Support clearance management strategies that minimize inventory surplus without compromising the fan-facing product assortment.
Deliver decision-support tools and stakeholder-facing reporting that translate complex models into actionable insights for operations and product teams.
Innovation & Problem Solving (Limitless Entrepreneurial Spirit)
Build and refine pricing, clearance, and network optimization models using discrete optimization techniques — including MIP, constraint solvers, and genetic algorithms — alongside simulation and heuristic methods.
Apply exploratory data analysis and statistical methods to uncover performance drivers, engineer predictive features, and inform model design decisions.
Develop scalable pipelines and automation tools using Python, Spark, and cloud infrastructure to operationalize models at scale.
Ownership & Execution (Determined & Relentless Mindset)
Own the full model development lifecycle — from problem framing and data engineering through training, evaluation, deployment, and monitoring — across supply chain and inventory initiatives.
Develop and maintain predictive models spanning forecasting, classification, regression, clustering, and segmentation in a production or operational environment.
Deliver consistently against business objectives in a fast-paced environment with frequently shifting priorities and requirements.
Take accountability for the measurable business impact of deployed models, tracking outcomes and iterating based on real-world performance.
AI & DIGITAL CAPABILITY
We are building a future-ready organization. This role is expected to:

Nice-to-haves

Experience with data visualization and BI tools such as Superset or Tableau for stakeholder-facing reporting.
Prior experience in retail, e-commerce, or supply chain domains.
Experience mentoring or guiding junior data scientists.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlaipythonsql

Platform: greenhouse
Effort: quick