Senior Data Scientist

Company: DataSpring

Location: Washington, DC (Remote)

Type: Full-time

Remote: Yes

Posted: 2026-06-22

About this role

Position Summary
The Senior Data Scientist is a highly skilled individual contributor responsible for leading advanced statistical and machine learning initiatives to solve complex business challenges using large-scale healthcare data. This role owns the end-to-end analytical process, including designing modeling approaches, developing and validating models, and translating business questions into technical solutions. The Senior Data Scientist partners closely with data engineering and cross-functional teams to operationalize models and ensure their performance and scalability in production environments. Success in this role requires strong technical judgment, the ability to communicate insights to diverse stakeholders, and a commitment to analytical rigor and reproducibility.


The Senior Data Scientist is a full-time, remote, exempt position and reports to the Sr. Director, Data Science & Advanced Analytics.


Specific Responsibilities

  • Lead the development, validation, and refinement of advanced statistical and machine learning models for complex business problems.
  • Serve as the primary analytical owner for assigned initiatives, with accountability for model quality, analytical rigor, and timely delivery of results.
  • Design analytical approaches and modeling strategies, translating business questions into well-defined technical solutions.
  • Perform advanced feature engineering, exploratory data analysis, and model evaluation using large, complex healthcare datasets.
  • Partner with Data Engineering and Information Systems teams to translate modeling approaches into production-ready solutions, while engineering teams own deployment and operations.
  • Support production models through performance analysis, monitoring, and retraining activities.
  • Design and execute experiments to test hypotheses and measure the impact of analytical solutions.
  • Evaluate new data sources and assess their suitability, quality, and limitations for modeling and analys...

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