Machine Learning Data Analyst

About Hello HeartHello Heart is the only digital therapeutics company to focus exclusively on heart disease, the leading cause of death for U.S. adults. Through a connected device and mobile app that uses AI, behavioral science, and personalized digital coaching to drive lifestyle changes, Hello Heart empowers people to embrace healthier behavior, which can reduce the risks of high blood pressure and heart disease. It also helps users catch blood pressure readings that are extremely high and encourages them to talk to their doctor to identify potential risk in time. Validated in peer-reviewed studies and trusted by leading Fortune 500 companies, Hello Heart is easy to use and works alongside an employer’s benefits ecosystem. Founded in 2013, Hello Heart is a member of the American Heart Association’s Innovators’ Network and is part of the CVS Health Point Solutions Management program. Hello Heart is backed by leading VCs including Stripes, Khosla Ventures, IVP, Blue Run and Resolute. Visit www.helloheart.com for more information.Hello Heart is seeking a talented and motivated Machine Learning Data Analyst to join our Users Data Science team. As a Machine Learning Data Analyst, you will be responsible for conducting in-depth analysis of our data science products, from research to production. Your work will directly contribute to improving healthcare practices and enhancing the well-being of individuals.Your Responsibilities

• Apply statistical analysis techniques, data mining algorithms, and visualization methods to extract meaningful patterns and trends from complex datasets.
• Monitor & analyze our models performance in production, generate insights and research leads for model improvements and new data driven solutions
• Conduct AB tests, analyze the impact of models on users behavior, taking into account cause/effect, treatment/prevention relationships.
• Collaborate closely with cross-functional teams, including data scientists, data engineers, product managers, and healthcare professionals, to translate research findings into impactful digital solutions.
• Stay updated with the latest research papers, advancements, and best practices in the field of healthcare analytics.

• 2+ years of hands-on experience
• Bachelor's degree in statistics, computer science, engineering or another related field.
• Strong analytical and critical thinking skills, with the ability to interpret complex data and generate meaningful insights.
• Proficiency in statistical analysis tools (e.g., R, or Python with libraries like Pandas, NumPy, and SciPy) and data visualization techniques.
• Strong knowledge and experience with SQL
• Familiarity with research methodologies, experimental design, and statistical modeling techniques (bayesian methods, propensity score matching, etc).
• Experience in analyzing esting the performance of ML models in production
• Advantage for candidate with experience in recommendation systems, user behavior segmentation, conducting AB tests for ML models in production, modeling the causal effects of treatment interventions