The Data Science team helps shape strategy at Included Health by turning data into product, operational, and business decisions that advance the Quintuple Aim of healthcare: better member experience, stronger outcomes, lower costs, clinician well-being, and health equity. We partner closely with product, engineering, clinical, operations, and finance to understand member needs, improve features, and drive impact across the business.
We’re looking for a Data Scientist II with strong analytical judgment, business intuition, and the ability to: frame ambiguous problems, define success metrics, work cross-functionally, and deliver clear recommendations that influence decisions. This is a great opportunity for someone who is excited by healthcare, motivated by impact, and eager to build expertise across multiple domains.
What You'll Do
Drive insight generation for complex projects both independently and in collaboration with cross-functional teams.
Develop models of cost and quality in support of our navigation and match services
Identify opportunities to better engage and navigate members so that we can drive top quartile outcomes at bottom quartile costs.
Develop a deep understanding of how our products are being used and identify opportunities to better serve our members’ needs.
Prototype novel approaches to measuring or inferring product and business performance.
Scale our impact so we can bring our services to more people in need.
What We're Looking For
5+ years of work experience in highly quantitative roles or equivalent and relevant advanced degrees.
Ability to effectively communicate complex quantitative patterns into robust narratives to support business decisions.
Strong proficiency in SQL and one or more programming languages (Python, R)
Experience designing and analyzing product experiments (A/B testing) including defining success metrics, interpreting results, and translating findings
Ability to independently drive results working on complex, ambiguous projects with a major quantitative component.
You thrive within collaborative environments and working with teams that include Product and Engineering.
Nice To Have
Previous experience in digital health or a high-growth startup
Experience building internal tools or infrastructure to support machine learning experimentation and deployment.
Experience developing data products leveraging Large Language Models (LLMs)