Lead Data Scientist

ABOUT FANDUEL

Fan Duel Group is the premier mobile gaming company in the United States and Canada. Fan Duel Group consists of a portfolio of leading brands across mobile wagering including:
America's #1 Sports book, Fan Duel Sports book; its leading iGaming platform, Fan Duel Casino; the industry's unquestioned leader in horse racing and advance-deposit wagering, Fan Duel Racing; and its daily fantasy sports product.

In addition, Fan Duel Group operates Fan Duel TV, its broadly distributed linear cable television network and Fan Duel TV+, its leading direct-to-consumer OTT platform. Fan Duel Group has a presence across all 50 states, Canada, and Puerto Rico.

The company is based in New York with US offices in Los Angeles, Atlanta, and Jersey City, as well as global offices in Canada and Scotland. The company's affiliates have offices worldwide, including in Ireland, Portugal, Romania, and Australia.

Fan Duel Group is a subsidiary of Flutter Entertainment, the world's largest sports betting and gaming operator with a portfolio of globally recognized brands and traded on the New York Stock Exchange (NYSE: FLUT).

THE POSITIONOur roster has an opening with your name on it

Fan Duel is looking for a Lead Data Scientist who specializes in customer behavior modeling and personalization to join our team. In this role you will develop and implement advanced recommendation and ranking models that power personalized Sports book and Casino experiences, and build a deep understanding of customer behavior through the marketing, product, and analytics lens. This role requires a strong background in data science, modern deep learning, and large-scale customer analytics.

You will own open-ended, ambiguous problems end-to-end-from ideation and problem formulation, through model research and offline evaluation, to partnering with ML Engineering on production deployment and post-launch iteration.

In addition to the specific responsibilities outlined above, employees may be required to perform other such duties as assigned by the Company. This ensures operational flexibility and allows the Company to meet evolving business needs.

THE GAME PLAN
Everyone on our team has a part to play

• Develop and deploy large-scale recommendation, retrieval, and ranking models (e.g., deep learning with embeddings and transformers) to drive personalized Sports book and Casino experiences across business units.
• Define and evolve the technical architecture for modern personalization systems (feature pipelines, candidate generation, ranking, feedback loops), partnering closely with ML Engineers and Data Engineering.
• Perform analysis on large and complex data sets utilizing relevant tools (SQL, Python, Spark) and provide strategic contributions
• Use statistical and machine learning techniques to segment users and predict future behaviors, developing automated logic and decision algorithms to deliver a better experience to the customer
• Lead projects from start to finish, set proper expectations, and collaborate with other data scientists, ML engineers, and product managers to communicate technical findings and support data driven decision making
• Oversee the integration and deployment of cross-functional and cross-organizational projects, developing process improvements and technical leadership
• Stay up to date on the latest advancements in data science and leverage cutting edge technology
• Mentor, brainstorm with, and enable others within the DS team and broader Data organization

THE STATS
What we're looking for in our next teammate

• Bachelor's degree in a highly numerate field (Computer Science, Mathematics, Statistics, Engineering, Economics, or related).
  MS or PhD in a relevant field strongly preferred:
• PhD candidates: demonstrated research in deep neural networks (e.g., representation learning, sequence modeling, transformers) and applications to recommendation / ranking or related problems.
• MS candidates: substantial industry experience working with Engineering and Product to design, ship, and iterate on machine-learning-powered products.
• 7+ years of applied data science experience (or equivalent research/industry combination) creating and deploying models in production environments.
• Hands on experience working in customer personalization and a strong understanding of the technical elements required in building and maintaining advanced models
• Strong practical experience with modern deep learning for personalization, including embeddings, sequence models, and transformers (experience with CNNs or other neural architectures is a plus).
• Experience in experimentation to validate models' impact and ability to quantify that impact
• Experience using user behavioral, promotional and marketing data in model building
• Proficiency in SQL and Python
• Experience with tech stacks such as MLFlow, Spark, and Databricks
• Can write production level code, understand principles of programming
• Comfortable with ambiguity and complexity
• Interest in Sports and/or Sports Gaming preferred

PLAYER BENEFITS
We treat our…