Note: The job is a remote job and is open to candidates in USA. DataSpring is the trusted data connector at the core of healthcare, and they are seeking a Senior Data Scientist to lead advanced statistical and machine learning initiatives using large-scale healthcare data. This role involves owning the analytical process, partnering with engineering teams, and ensuring model performance and scalability in production environments.
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 analysis
- Communicate analytical findings, model behavior, and key assumptions to stakeholders with varying levels of technical expertise
- Document analytical methods, decisions, and results to support reproducibility and knowledge sharing
- Provide peer-level technical guidance and code review to Data Scientists and Analysts, supporting their development without formal leadership responsibility
- Contribute reusable code, features, and analytical assets to shared repositories and team standards
Skills
- 4–7 years of experience building statistical or machine learning models using large datasets
- Advanced degree in Computer Science, Engineering or relevant field
- Advanced proficiency in Python, R, and SQL for statistical analysis, modeling, and feature engineering
- Strong hands-on experience with statistical and machine learning techniques, including regression/GLM, tree-based methods, boosting, clustering, and basic text analytics
- Proven experience developing, validating, and tuning models for real-world use cases
- Experience supporting models in production environments, including collaboration with engineers on deployment and monitoring
- Solid understanding of model evaluation, experimental design, and performance metrics
- Strong data wrangling skills and experience working with large, complex datasets
- Ability to create clear, compelling data visualizations and analytical narratives using tools such as Power BI, Tableau, or R/Shiny
- Ability to translate business problems into analytical approaches with limited guidance
- Strong written and verbal communication skills for working effectively with cross-functional stakeholders
- Experience following best practices for reproducible research, version control, and documentation
- Ability to provide constructive peer feedback and informal mentorship
- Demonstrated curiosity and willingness to learn new tools, methods, and domains
- PhD in Data Science or another quantitative field
Benefits
- Medical, dental, and vision coverage
- A 401(k) with company contributions and matching
- Paid parental leave
- Tuition assistance
- Generous paid time off
Company Overview