Data Scientist

Oscar’s Data team is focused on pushing our understanding of this complex landscape of health care and insurance business

Insurance companies sit on a trove of data that is both broad and deep, spanning financial claims, clinical medical records, and rich product interaction data from our members

Connecting the dots across these datasets gives us unique insight into how the healthcare system functions and allows us to improve care coordination, better manage risk, build higher-performing provider networks, and create a standout consumer experience in our product

We’re hiring several Data Scientists to support data science initiatives across multiple teams

In this role, you’ll contribute to the development and maintenance of data pipelines, analytical models, and validation processes that power business decision-making

You will report into a leader on the Data team (Senior Data Scientist and above)

This posting is representative of multiple roles, and final team placement will be determined during the interview process

Build, maintain, and support data pipelines to ensure reliable, accurate, and timely data delivery

Assist with the testing, validation, and refinement of statistical or analytical models

Perform advanced analytical work and validation checks on datasets and model outputs

Identify data quality issues, anomalies, or inconsistencies and help implement corrective solutions

Collaborate with data leaders and cross-functional business partners to understand data needs and improve processes

Partner closely with business, engineering, product and data stakeholders to deliver impactful solutions

Write clear, maintainable analytical code and documentation

Follow established data science standards, best practices, and compliance requirements- This position is well-suited for early-career data scientists who have strong technical foundations and are excited to grow their skills while working on real-world data problems in a collaborative environment

1+ years of experience working with SQL or intermediate Python (for example, working with multiple data sources)

Bachelor’s degree in a technical or quantitative field or 1+ year of relevant professional experience

1+ years of experience building data models and using more advanced analytics methods, including conducting in depth analysis, rather than simple descriptive analysis

Master’s degree in a technical or quantitative field

Exposure to statistical modeling, machine learning, or large-scale data processing

Experience in healthcare, health insurance, or other regulated industries