PrizePicks

Data Science Engineer

Full-time
$100k+/mo
a month ago
154 views

Data Analyst

Python

Git

Kubernetes

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

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

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.