PrizePicks
PrizePicks is the fastest-growing sports company in North America according to the 2023 Inc. 5000 rankings, two years running, and the largest independent skill-based fantasy sports operator in the country.
Spectator Sports
201 - 500
Data Science Engineer
4 days ago
🏡 Remote – Anywhere in California
PrizePicks
PrizePicks is the fastest-growing sports company in North America according to the 2023 Inc. 5000 rankings, two years running, and the largest independent skill-based fantasy sports operator in the country.
Spectator Sports
201 - 500
Description
•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.
Requirements
•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
Benefits
•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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