Join PrizePicks: The Fastest Growing Sports Company in North America

At PrizePicks, recognized by Inc. 5000, we are the fastest growing sports company in North America. As the leading platform for Daily Fantasy Sports, we cover a diverse range of sports leagues including the NFL, NBA, and Esports titles like League of Legends and Counter-Strike.

Our inclusive team of over 450 employees thrives in a culture that values diversity and individualism, regardless of your level of sports fandom. Ready to reimagine the Daily Fantasy Sports industry with us?

About the Role: Engineering Manager — Data Science Engineering

The PrizePicks Analytics Team is at the heart of our operations, responsible for building and maintaining analytical tools and products that support our business across all departments. As the Engineering Manager — Data Science Engineering, you will lead a team to develop, test, maintain, and evolve initiatives in streaming data, productionized algorithms, and MLOps infrastructure to enhance PrizePicks’ digital offerings.

Responsibilities

As an Engineering Manager, you will:

• Lead a team to create and maintain sport and user data stream architecture, ensuring data reliability in speed and quality for both raw and transformed data pipelines.
• Collaborate with our Data Science team to operationalize DS/ML assets, ensuring high-quality, stable, and scalable model outputs.
• Oversee the design, implementation, and deployment of the data, MLOps, and API stack required for real-time pricing models, personalization, risk management tooling, and other essential functions.
• Work cross-functionally with Engineering, QA, and Product teams to create and distribute real-time data products to the PrizePicks platform.
• Enable teams to build and own monitoring and alerting services, ensuring stability and uptime of production services by working with Engineering and DevOps teams.
• Solidify and disseminate information through rigorous documentation, roadmaps, and knowledge transfer processes across teams.
• Act as a thought leader, implementing novel technologies and best practices.

Qualifications

Track Record

• 5+ years in a people leadership role, managing and growing a team of Data Science Engineers/Machine Learning Engineers/ML-focused Software Engineers.
• Extensive experience working cross-functionally with data engineering, data science, product, and engineering teams, as well as external data providers and 3rd party services.
• Proven experience in shipping and maintaining production-grade systems for internal tools and product users.

Role Specific

• Experience with simulation frameworks, personalization, and/or near real-time consumer-facing machine learning implementations.
• Strong understanding of software development life cycle principles related to shipping critical and always-on cloud services.
• Experience/familiarity with technologies including SQL/NoSQL databases, scripting languages (SQL, Python), GCP services, ML frameworks (sci-kit-learn, PyTorch, TensorFlow), and more.
• Knowledge of data pipeline and workflow tools like Prefect, Airflow, Cloud Workflows, and monitoring platforms like Datadog and ELK stack.
• Exposure to Infrastructure as Code platforms like Terraform and Google Cloud Deployment Manager.

Industry Specific

• Passion for daily fantasy sports and understanding of the users, data, and competitive landscape.

Personal Attributes

• Experience in purposeful people growth, mentorship, and coaching.
• Excellent organizational, communication, presentation, and collaboration skills.
• Graduate degree in Computer Science, Statistics, Mathematics, Informatics, Information Systems, or a related field. Advanced degree preferred.

What Makes You Stand Out

• Experience building with or leading a team using Rust, Go, or other high-performance programming languages.
• Experience building real-time production data science pipelines in a daily fantasy sports or odds-making business.
• Experience shipping products in both D2C and B2B SaaS operational spaces.
• Experience deploying and upholding regulated data products.

Location and Remuneration

This is a remote position with occasional travel