Senior Data Scientist, Product Analytics

Hello Heart is on a mission to make heart attacks a thing of the past.

We’re an AI company focused exclusively on heart health, building a platform that predicts and prevents cardiac events before they happen—identifying risk up to 10 days in advance versus 10 years in traditional clinical models. 

This is already working at scale. Hello Heart has been shown to reduce inpatient hospital days by 47% and deliver ~$1,800 in annual savings per member. Hello Heart is the cardiac prevention partner to over 80% of large U.S. health plans and serves hundreds of public and private employers.

We’re defining how the #1 cause of death—heart disease—is managed in the AI era. Join us.

Hello Heart is seeking a talented and impact-driven Data Scientist to join our ML team. In this role, you will shape the future of the digital health products that help people understand and improve their heart health. By applying your technical skills, analytical mindset, and product intuition to rich real-world health and behavioral data, you will help define the experiences we build for our users and the value we deliver to employers and health plans.

You will collaborate with a wide range of cross-functional partners across Product, Engineering, Data Science, Data Engineering, Clinical, Marketing, and Customer Success. You will use data and analysis to identify and solve our biggest product challenges, influence product strategy and investment decisions, and translate insights into digital solutions that improve the well-being of the people we serve.

• →Product leadership: Use data to shape product development, quantify new opportunities, and identify upcoming challenges. Help your partner teams prioritize what to build, set goals, and understand their product's ecosystem, ensuring what we build brings real value to users, clients, and Hello Heart.
• →Analytics: Guide teams with data and insights. Develop hypotheses and test them using a varied toolkit of rigorous analytical approaches, from experimentation to causal inference and statistical modeling.
• →Communication and influence: Don't just present data, tell data-driven stories. Influence partners with clear insights and recommendations, and become a trusted strategic partner through structure and clarity.

• →Work with large and complex datasets, applying statistical analysis and visualization methods to extract meaningful patterns and trends.
• →Identify and measure the success of product efforts through goal setting, forecasting, and monitoring of key product and engagement metrics.
• →Design, execute, and analyze A/B tests, including tests of ML-driven features, accounting for cause/effect and treatment/prevention relationships.
• →Monitor and analyze the performance of our ML models in production, and generate insights and research leads for model improvements and new data-driven solutions.
• →Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.
• →Partner with Product, Engineering, Data Science, and healthcare professionals to inform and execute product strategy.
• →Integrate AI tools into your workflows to drive measurable gains in efficiency and quality.
• →Stay current with the latest research and best practices in healthcare analytics and AI.

• Bachelor's degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative field.
• 4+ years of hands-on experience in analytics or data science, solving analytical problems using quantitative approaches.
• Proven experience leading data-driven projects from definition to execution, including defining metrics, designing experiments, and communicating actionable insights.
• Strong knowledge and experience with SQL.
• Proficiency in Python (Pandas, NumPy, SciPy) and in data visualization.
• Familiarity with experimental design and statistical modeling techniques (e.g., Bayesian methods, propensity score matching).
• Experience analyzing or testing the performance of ML models in production.
• Hands-on experience using AI tools to support data analysis, coding, research, and problem solving.
• Strong analytical and critical thinking skills, with excellent communication and storytelling ability.