FanDuel is looking to solve the problem of developing and implementing advanced recommendation and ranking models to power personalized Sportsbook and Casino experiences, and building a deep understanding of customer behavior through the marketing, product, and analytics lens.
Requirements
- 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
Responsibilities
- Develop and deploy large-scale recommendation, retrieval, and ranking models (e.g., deep learning with embeddings and transformers) to drive personalized Sportsbook 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
Other
- Bachelor’s degree in a highly numerate field (Computer Science, Mathematics, Statistics, Engineering, Economics, or related).
- 7+ years of applied data science experience (or equivalent research/industry combination) creating and deploying models in production environments.
- Comfortable with ambiguity and complexity
- Interest in Sports and/or Sports Gaming preferred
- MS or PhD in a relevant field strongly preferred
