Junior Data Scientist

**The Company:** Ilant Health is a value-based healthcare provider focused on cardiometabolic obesity, a group of interconnected conditions that drive over $700 billion in annual U.S. healthcare expenses. We are dedicated to increasing access to treatment while reducing the total cost of care for employers and payers. We are not just a provider, we are a technology-enabled practice driven by analytics. Our mission is to "de-average" care, using proprietary algorithms to match Members with the right interventions at the right time, while establishing habits that support treatment success and sustained outcomes. By combining clinical rigor with a consumer-grade digital experience, we drive life-changing outcomes and measurable ROI. We serve as the single, integrated front door for comprehensive care, delivering a full continuum of evidence-based solutions, spanning bariatric surgery, pharmacotherapy, and intensive behavioral therapy. Crucially, we personalize care for every Member through a dedicated multidisciplinary care team, empowered by our advanced digital platform. This ecosystem includes specialized tools for our providers and a fully accessible Member Portal (web and mobile) for our Members. **The Role:** We are seeking a Data Scientist to help build intelligent tools and data products that improve operational efficiency across Ilant Health. This is an ideal role for an early-career data scientist who enjoys solving business problems with data, automation, and Generative AI. You'll work closely with Product, Engineering, Clinical Operations, Client Success, and Analytics to identify manual workflows, build predictive models and AI-powered solutions, and create tools that enable our teams to work smarter as we scale. This is a highly cross-functional role that blends analytics, software development, and experimentation. The ideal candidate is curious, technically strong, eager to learn, and excited about applying machine learning and large language models (LLMs) to real-world healthcare operations. **Key Responsibilities:** - Identify opportunities to improve operational efficiency through data science, automation, and AI-powered solutions. - Build internal tools and prototypes using Python, SQL, and Generative AI technologies to streamline business processes. - Develop predictive models, analytical frameworks, and decision-support tools that improve operational and clinical workflows. - Design, test, and iterate on LLM-powered applications, including copilots, workflow automation, document processing, and knowledge retrieval tools. - Analyze operational, clinical, and product data to identify trends, generate insights, and recommend process improvements. - Build dashboards, reporting assets, and data visualizations to monitor operational performance and measure the impact of new solutions. - Collaborate with Product, Engineering, Clinical Operations, and Client Success to translate business needs into technical solutions. - Partner with Data Engineering to develop scalable data models and production-ready analytics workflows. - Contribute to experimentation, rapid prototyping, and evaluation of emerging AI technologies and machine learning techniques. - Document methodologies, maintain reproducible workflows, and contribute to data quality and governance best practices. - Technical Environment - Python for analytics, automation, and machine learning - SQL and Snowflake data warehouse - dbt for data modeling and transformation - Large Language Models (OpenAI, Anthropic, or similar APIs) - BI tools such as Tableau, Looker, Power BI, or Metabase - Git and modern software development practices **Qualifications:** - 1–3 years of experience in Data Science, Analytics, Machine Learning, or a related technical field. - Strong programming skills in Python and SQL. - Experience building analytical models, automations, or internal tools using data. - Familiarity with machine learning concepts and experience applying statistical o…