Data Scientist, Oscar Health

• 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
• Bachelor’s degree in a technical or quantitative field or 1+ year of relevant professional experience
• 1+ years of experience working with SQL or intermediate Python (for example, working with multiple data sources)
• 1+ years of experience building data models and using more advanced analytics methods, including conducting in depth analysis, rather than simple descriptive analysis

Desirable

• 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