Senior Data Scientist

About the Team

Fanatics is one of the world’s most transformative companies, which over the past decade has implemented a revolutionary vertical commerce model, cutting-edge tech platform and agile supply chain to morph from a North American e-commerce vendor into a new breed of mobile-first consumer brand: part tech company, part on‑demand manufacturer and part logistics expert. Fanatics’ commerce division is the world’s largest manufacturer and provider of licensed sports merchandise, and the same innovation and differentiation the company applied to the antiquated licensed apparel industry is now being optimized across the entire sports ecosystem, including physical and digital trading cards and collectibles and online sports betting and iGaming.

With more choices at the fingertips of consumers than ever before, Fanatics is building the leading global digital sports platform to create interactive, lasting fan experiences which also help partners establish better direct‑to‑consumer relationships in today’s highly competitive world.

We are looking for senior‑level Data Scientists to join our Data Engineering, Science, and Analytics team. As a data scientist, you will have ample opportunities to apply your data science skillset to unlock vast business opportunities by extracting key insights using a wide range of data sources, advanced statistical models, and machine learning algorithms and translating results into meaningful, goal‑oriented business actions.

Each day, you will be presented with a variety of new challenges and interesting projects that tap your interests and strengths.

• Collaborate with cross‑functional partners in operations, finance, marketing, and engineering to understand business need and scope data science projects.
• Wrangle, process, cleanse, verify, and enrich data from different sources used for analysis.
• Help build data‑informed business strategy and roadmaps.
• Translate business needs into data product requirements, evaluate technologies, and identify opportunities to innovate and improve our 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 closely with data engineers to create services that can ingest and supply data to and from both internal and external sources and ensure data quality and timeliness.
• Lead the development of data visualization and dashboards to help the organization monitor performance, generate insights, and continuously improve user experience.
• Establish playbooks to drive process and consistent outcomes.
• Participate in the full life cycle of model development, which spans from business problem discovery, data discovery to model deployment and monitoring.

• Master’s or Doctoral degree in Computer Science (with a focus on Data Mining, Machine Learning), Statistics, Econometrics, Physics, or other rigorous quantitative disciplines that require processing and modeling data at a complex and large scale.
• 4+ years of professional experience as a data scientist.
• Proficient in Python, SQL, Spark, the associated Python and Spark packages commonly used by data scientists, and Deep Learning libraries, such as PyTorch.
• Proficient in data wrangling and exploratory analysis, with the ability to extract meaningful insights from complex datasets and establish robust data foundations for downstream modeling efforts.
• Strong understanding of and practical experience in a wide range of machine learning algorithms and statistical modeling and inference. Experiences with Generative AI/LLM application is a strong plus.
• Experience and knowledge with computer vision domain, libraries such as OpenCV, PIL, and modern CV architectures (CNNs, Vision Transformers, Image Gen AI etc.) is preferred.
• Experience in software development, system design and deployment is preferred.
• Working experience in cloud‑native technology.
• Experience working with large structured and unstructured datasets stored in relational and NO‑SQL databases.
• Out‑of‑the‑box thinker and problem solver who can turn ambiguous business problems…