Senior Data Science Engineer

Summary

Join PrizePicks, a rapidly growing sports company, as a Senior Data Science Engineer. You will play a key role in developing and maintaining analytics tools and workflows, focusing on streaming data and MLOps infrastructure. Responsibilities include creating and maintaining data stream architecture, partnering with Data Science to operationalize models, designing and implementing data and MLOps stacks for real-time pricing and other critical functions, collaborating with cross-functional teams, building monitoring processes, and acting as a thought leader within the organization. This role requires extensive experience in backend engineering, machine learning engineering, and working with large-scale data streaming pipelines. A graduate degree in a quantitative field and excellent communication skills are essential. PrizePicks offers a competitive salary, comprehensive benefits, and a flexible work environment.

Requirements

• 5+ years of experience in Backend Engineering/Machine Learning Engineering, shipping and maintaining production-grade systems for internal tools and product users
• 2+ years of experience acting as technical lead and providing mentorship and feedback to junior engineers and scientists
• Extensive experience exposing real-time predictive model outputs to production-grade systems, leveraging large-scale cloud-based data streaming pipelines and infrastructure
• Extensive experience working cross-functionally with data engineering, data science, product, and engineering teams, as well as external data providers and 3rd party services
• Experience in most of the following: SQL/NoSQL databases/warehouses: Postgres, BigQuery, BigTable
• Scripting languages: SQL, Python, Go, Rust
• Cloud platform services in GCP and analogous systems: Cloud Storage, Cloud Compute Engine, Cloud Functions, Kubernetes Engine
• Code version control: Git
• Code testing libraries: PyTest, PyUnit, etc
• Common ML and DL frameworks: scikit-learn, PyTorch, Tensorflow
• Modeling methods: classical ML techniques, deep learning, gradient boosting, bayesian methods, generative models
• MLOps tools: DataBricks, MLFlow, Kubeflow, DVC
• Data pipeline and workflow tools: Airflow, Argo Workflows, Cloud Workflows, Cloud Composer, Serverless Framework
• Monitoring and Observability platforms: Prometheus, Grafana, Datadog, ELK stack
• Infrastructure as Code platforms: Terraform, Google Cloud Deployment Manager
• Other platform tools such as Redis, FastAPI, Docker and data visualization tools such as Streamlit or Dash
• Excellent organizational, communication, presentation, and collaboration experience with organizational technical and non-technical teams
• Graduate degree in Computer Science, Statistics, Mathematics, Informatics, Information Systems or other quantitative field

Responsibilities

• Create and maintain optimal sport data stream architecture, ensuring data reliability in both speed and quality for both raw and transformed data pipelines
• Partner with Data Science to determine best paths for operationalization of DS/ML assets, ensuring model output quality, stability, and scalability
• Steer the design, implementation, and deployment of the data, MLOps, and API stack required for real-time pricing models, personalization/recommendations, risk management tooling, and other critical functions by contributing to architecture evaluations and decisions for the evolving data product roadmap
• Partner cross-functionally with Engineering, QA, and Product teams to enable the creation and distribution of highly-visible and real-time data products to the PrizePicks platform
• Build and own rigorous monitoring, alerting, and documentation processes, and work with Engineering teams to ensure complete feature uptime
• Grow as a thought leader in the broader PrizePicks technology org, staying abreast of and implementing novel technologies, and disseminating knowledge and best practices to junior members of the team and collaborators alike

Preferred Qualifications

Experience building real-time production data science pipelines in a daily fantasy sports or oddsmaking business

Benefits

• Company-subsidized medical, dental, & vision plans
• 401(k) plan with company match
• Annual bonus
• Flexible PTO to encourage a healthy work/life balance (2 weeks STRONGLY encouraged!)
• Generous paid leave programs, including 16-week paid parental leave and disability benefits
• Workplace flexibility and modern work schedules focused on getting the job done, not hours clocked
• Company-wide in-person events and team outings
• Lifestyle enhancement program
• Company equipment provided (Windows & Mac options)
• Annual performance reviews with opportunities for growth and career development