Role Overview

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.

Requirements

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.

Tech Stack

ETL
Python
SQL

Benefits

full health benefits (medical, dental, and vision)
flexible spending and health savings accounts
company paid life insurance
company paid short-term and long-term disability
company equity
voluntary benefits
401(k)
company paid holidays
flexible time off
employee wellness program (“Breathe”)

Tendo

Open Positions (1)

Data

Principal Data Scientist