Senior Data Scientist

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The Senior Data Scientist will support Tendo analytics projects focused on quality management and risk adjustment. The person in this role will access data from multiple sources (public and private) and translate it into information that is meaningful and actionable for health systems. The Senior Data Scientist develops, maintains, and enhances predictive models that improve products in several areas including, but not limited to quality, risk, and operational efficiency.

We’re looking for someone who brings an AI‑native mindset, has hands‑on experience applying AI or machine learning to real‑world problems, and is passionate about exploring how emerging AI capabilities can improve healthcare delivery and outcomes. In addition, the Senior Data Scientist will also have the opportunity to ask novel, data‑driven questions and drive new analyses.

Make an impact—join our team! We’re a fast‑growing, mission‑driven company building a culture that enables teams and individuals to thrive. Our team‑driven culture and rapid growth have earned us recognition as one of Forbes’ Top Startup Employers for both 2024 and 2025. Led by an experienced and proven team, we live by our values and are always on the hunt for motivated people with diverse experiences and backgrounds to help us improve the care journey for patients, clinicians, and caregivers by creating software that provides seamless, intuitive, and user‑friendly experiences.

If you like working with innovative technologies and want to be part of a growing team that will help transform the healthcare experience, we encourage you to apply today!

Tendo has hubs in San Francisco, CA;
San Diego, CA;
Salt Lake City, UT;
Chicago, IL;
Nashville, TN; and Philadelphia, PA. Candidates may be located in any one of our hub locations.

Mid‑Senior level

Full‑time

Engineering and Information Technology

Software Development

• Analyze data from multiple databases to drive optimization and improvement of quality outcomes, resource utilization, and risk adjustment.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling to increase and optimize patient outcomes, patient experiences, risk adjustment opportunities, and other business outcomes.
• Explore and experiment with emerging AI technologies to evaluate their applicability in solving healthcare problems and improving operational workflows.
• Develop analytic data sets and use statistical software to analyze data sets as requested.
• Use third‑party software tools in the development of queries and visualizations.
• Coordinate with different functional teams to implement models and monitor outcomes.

• Bachelor’s degree in data science, statistics, epidemiology, engineering, information science, computer science, or equivalent technical experience.
• Hands‑on experience writing Python code including, but not limited to, machine learning, data science and engineering, and ETL pipelines.
• 5+ years of experience in data analysis software, with data science experience preferred.
• 5+ years of experience with Git Hub/Git, Python, SQL, statistics, and ML modeling.
• Track record of applying AI or ML models to solve practical, real‑world problems—ideally in healthcare or similar complex domains.
• Knowledge of statistical concepts and data mining methods such as hypothesis testing (or A/B testing), distribution analysis, Bayesian estimation, linear and logistic regression, GLMs, text mining, time series analysis, etc.
• Knowledge of a variety of traditional machine learning techniques such as feature engineering methods for large‑scale numerical and categorical data, dimensionality reduction, clustering, decision trees/random forests/gradient boosted decision trees, deep learning.
• Knowledge of machine learning implementation strategies such as proper and thorough evaluation of ML models in production, detecting data/covariate/concept drift, leveraging feature stores and model registries, deploying models as REST…