Top Healthtech Data Science Jobs

Lead data science projects to analyze complex dental and clinical datasets, build and validate statistical and predictive models, define KPIs, productionize ML with engineering/ML teams, communicate findings to stakeholders, and mentor junior data scientists to improve product and clinical impact.

The Manager of Advanced Analytics will lead the design and implementation of data solutions, mentor team members, and collaborate with stakeholders to drive analytics strategy and improvements in patient outcomes.

Hands-on senior data scientist role for PBM analytics to build, deploy, and monitor ML/DL models at scale, perform large-scale SQL analyses on prescription claims, ensure data quality and feature engineering, collaborate with engineering and MLOps to productionize models, communicate results to business leaders, and mentor peers.

As a Founding Data Scientist, you will develop predictive models and optimize data infrastructure to enhance supply chain operations, focusing on shipment risk and decision-making.

Perform healthcare data extraction, analysis, predictive modeling, and reporting to support reimbursement policy, provider negotiations, value-based care, utilization management, and cost containment. Develop analytic processes, BI tools and financial impact models; present results to stakeholders and mentor junior analysts.

The Senior Principal Statistician leads statistical strategies in clinical trials, ensuring scientific rigor and regulatory compliance while mentoring junior staff and contributing to drug development.

The Risk Data Scientist will develop adaptive decisioning models for risk assessment in financial transactions, focusing on fraud detection and compliance, while managing model governance and deployment in a regulated environment.

As a Senior Data Scientist at Oscar, you will develop ML frameworks and data models to enhance member experience in health insurance, collaborating closely with cross-functional teams and managing team roadmaps.

Lead analytics and data science initiatives to generate prospect insights, build statistical models and machine learning solutions, create self-service dashboards, integrate external and multi-source data, support decision-making, and provide ad hoc analyses to advance departmental strategies.

Collect, clean, and analyze large healthcare datasets; build, test, and deploy statistical and machine learning models; develop scalable data pipelines; create visualizations and dashboards; collaborate with cross-functional teams; document methods and stay current with data science best practices.