Applied Scientist — ML, Experimentation & Decision Systems

📋 Description

• • Everlywell, a leader in digital health and biomarker intelligence, is seeking a highly skilled and motivated Applied Scientist to join our innovative team in Austin, TX. This pivotal role is centered around the development, implementation, and rigorous evaluation of Machine Learning (ML) systems that are fundamental to powering our large-scale health engagement programs. These programs are designed to drive crucial care actions among health plan members, ranging from the completion of diagnostic kits to the utilization of preventive and virtual care services. As an Applied Scientist, you will be at the forefront of leveraging AI and ML to transform complex biomarker data into actionable, life-changing health insights, thereby reshaping the landscape of healthcare delivery.
• • In this capacity, you will be instrumental in building and measuring the ML systems that underpin these critical health engagement initiatives. Your responsibilities will span the entire ML lifecycle, from initial model training and performance evaluation to the meticulous design and execution of A/B tests. You will collaborate closely with engineering and business stakeholders to identify opportunities for improvement and to drive tangible enhancements in real-world health outcomes for millions of individuals. This is a unique opportunity to apply your expertise in ML and experimentation to systems that have a direct and significant impact on member health at an unprecedented scale.
• • The role demands a hands-on approach to modeling, a deep commitment to rigorous experimentation, and a passion for building robust systems that enhance decision-making processes in a production environment. You will tackle practical, production-facing challenges that offer clear business value and provide strong cross-functional visibility. Furthermore, you will have the opportunity to influence and shape Everlywell's strategic application of both ML and AI within our operational workflows, contributing to our mission of making healthcare smarter, faster, and more personalized.
• • Key responsibilities will include developing and deploying predictive models to identify members who may benefit from specific health interventions or programs. You will design and analyze experiments to test hypotheses related to user engagement, program effectiveness, and the impact of ML-driven recommendations. This involves a deep understanding of statistical methods, causal inference, and experimental design principles to ensure the validity and reliability of test results. You will also be responsible for establishing and monitoring key performance indicators (KPIs) for ML models and systems, ensuring they meet performance targets and contribute positively to business objectives.
• • Furthermore, you will play a crucial role in the data pipeline and feature engineering processes, working with large datasets to extract meaningful features that improve model accuracy and relevance. This includes collaborating with data engineers to ensure data quality, accessibility, and efficient processing. You will also be expected to stay abreast of the latest advancements in ML, experimentation, and causal inference, and to proactively identify opportunities to integrate new techniques and technologies into Everlywell's systems.
• • The ideal candidate will possess a strong analytical mindset, excellent problem-solving skills, and the ability to translate complex technical concepts into clear, actionable insights for non-technical stakeholders. You will contribute to a culture of data-driven decision-making and continuous improvement, helping Everlywell to further its mission of democratizing access to personalized health insights and improving health outcomes for all.
• • This role offers a dynamic and challenging environment where you can make a significant contribution to a rapidly growing digital health company. You will work with cutting-edge technology, collaborate with a talented team of scientists, engineers, and product managers, and have the opportunity to grow your career in a field that is transforming healthcare. Your work will directly impact millions of lives by helping individuals take proactive steps towards better health.