Data Science Engineer

Data Science Engineer

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 Data Science Engineer, you will be developing, maintaining, and testing streaming data and MLOps infrastructures to enable PrizePicks to offer real-time priced markets 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 the 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.

What you have:

  • 3+ 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.
  • Experience building and optimizing cloud-based data streaming pipelines and infrastructure.
  • Experience exposing real-time predictive model outputs to production-grade systems leveraging large-scale
    distributed data processing and model training.
  • Experience with 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, Nose2, etc.
    • Common ML and DL frameworks: scikit-learn, PyTorch, Tensorflow
    • Modeling methods: classical ML techniques, deep learning, gradient boosting, bayesian methods,
      generative models.
    • Data pipeline and workflow tools: Prefect, Airflow, 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 Redis, FastAPI, Streamlit.
  • Strong 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

What makes you stand out:

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

Where you’ll live:

  • Anywhere in the US is fine but Atlanta would be preferred. 

Benefits you’ll receive:

In addition to your great compensation package, we’ll shower you with perks including: 

  • Company-subsidized medical, dental, & vision plans 
  • 401(k) plan with company match
  • Long-term incentives 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

 

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