Principal Data Scientist, Tendo

• 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
• 7+ years of experience in data analysis software, with data science experience preferred
• 7+ years of experience with GitHub/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 APIs, integrating models into products, etc
• Interest in staying current on AI advancements (e.g., generative AI, LLMs, foundation models), and enthusiasm for integrating new capabilities into analytical workflows
• Demonstrated proficiency in writing SQL queries on large, complex datasets for data analysis and analytics engineering
• Strong problem-solving skills with an emphasis on data analytics
• Excellent written and verbal communication skills for coordinating across teams

Desirable

• The Principal 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 Principal 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 Principal Data Scientist will also have the opportunity to ask novel, data-driven questions and drive new analyses
• 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