Staff Data Science Engineer
At PrizePicks, we are the fastest growing sports company in North America, as recognized by Inc. 5000. 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 team of over 400 employees thrives in an inclusive culture that values individuals from diverse backgrounds, regardless of their level of sports fandom. Ready to reimagine the DFS industry together?
The Analytics Team is responsible for building and maintaining analytics tools and workflows to support the PrizePicks business across all departments — at the core of these operations is data. As a Staff Data Science Engineer, you will be developing, maintaining, testing, and leading projects regarding streaming data and MLOps infrastructures to enable PrizePicks to offer real-time simulation based market pricing within the product.
What you’ll do:
- 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.
- Lead the design and implementation of the data and MLOps stack required for real-time pricing models and contribute to architecture evaluations and decisions for our growing data product roadmap.
- Work cross-functionally with Engineering, QA, and Product teams to enable the creation and distribution of highly-visible, real-time, in-game micro-market offerings to the PrizePicks platform.
- Empower teams to build and own rigorous monitoring, alerting, and documentation processes, and work with Engineering teams to ensure complete feature uptime.
- Act 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.
What you have:
- 7+ years of experience in a data science, machine learning engineer, or data-oriented software engineering role creating and pushing end-to-end data science pipelines and MLOps assets to production.
- 2+ years of experience acting as technical lead and providing mentorship and feedback to junior engineers and scientists.
- Extensive experience building and optimizing cloud-based data streaming pipelines and infrastructure.
- Extensive experience exposing real-time predictive model outputs to production-grade systems leveraging large-scale distributed data processing and model training.
- Experience in most of the following:
- SQL/NoSQL databases/warehouses: Postgres, BigQuery, BigTable.
- Scripting languages: SQL, Python.
- Cloud platform services in GCP and analogous systems: Cloud Storage, Cloud Compute Engine, Cloud Functions, Kubernetes Engine, Redis.
- Code version control: Git.
- Code testing libraries: PyTest, PyUnit, Nose2, etc.
- Common ML and DL frameworks: scikit-learn, PyTorch, Tensorflow.
- Modeling methods: classical ML techniques, exposure to deep learning, gradient boosting, bayesian methods, and generative models.
- Data pipeline and workflow tools: Prefect, Airflow, Cloud Workflows, Cloud Composer, Serverless Framework.
- Monitoring and Observability platforms: Datadog, ELK stack.
- Infrastructure as Code platforms: Terraform, Google Cloud Deployment Manager, Ansible.
- Other platform tools such as FastAPI.
- 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.
- Preferred: Experience building real-time production data science pipelines in a daily fantasy sports or odds-making business.
What makes you stand out:
- Experience with Rust, Go, or other high performance programming languages.
- Exposure to unit, integration, functional, and load testing libraries/tools.
- Experience with data visualization tools such as Streamlift or Dash.
- Experience building real-time production data science pipelines in a daily fantasy sports or odds-making business.
Where you’ll live:
Anywhere in the US is fine but Atlanta, Georgia would be preferred.
Benefits you’ll receive:
In addition to your great compensation package, company subsidized medical/dental/vision coverage plans and matching 401(k), we’ll shower you with perks including:
- Company-subsidized medical, dental, & vision plans
- 401(k) plan with company match
- Stock options and bi-annual bonus
- Uncapped PTO to encourage a healthy work/life balance (2-week MINIMUM required!)
- 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
You must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.
PrizePicks is an Equal Opportunity Employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
