Applied Scientist — ML, Experimentation & Decision Systems job opportunity at Everly Well, Inc..

Home Jobs In United States Tag: Experimentation & Decision Systems Applied Scientist — ML, Experimentation & Decision Systems position at Everly Well, Inc.


Date2026-03-06 bot
Everly Well, Inc. Applied Scientist — ML, Experimentation & Decision Systems
Experience: 5-years
Pattern: Full-Time
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Experimentation & Decision Systems

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loacation Austin, TX, United States
loacation Austin, TX....United States
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<p><span style="font-size: 16px;">Everlywell is a digital health company pioneering the next generation of biomarker intelligence—combining AI-powered technology with human insight to deliver personalized, actionable health answers. We transform complex biomarker data into life-changing insights—seamlessly integrating advanced diagnostics, virtual care, and patient engagement to reshape how and where health happens.</span></p> <p>&nbsp;</p> <p><span style="font-size: 16px;">Over the past decade, Everlywell has delivered close to 1 billion personalized health insights, transforming care for 60 million people and powering hundreds of enterprise partners. In 2024 alone, an estimated 1 in 86 U.S. households received an Everlywell test, solidifying our spot as the #1 at-home testing brand in the country. And we’re just getting started. Fueled by AI and built for scale, we’re breaking down barriers, closing care gaps, and unlocking a more connected healthcare experience that is smarter, faster, and more personalized.</span></p> <p>&nbsp;</p> <p><span style="font-size: 11pt;">Everlywell operates large-scale health engagement programs that help health plan members complete important care actions — from returning diagnostic kits to accessing preventive and virtual care.</span></p> <p>&nbsp;</p> <p><span style="font-size: 11pt;">We’re hiring an </span><strong style="font-size: 11pt;">Applied Scientist</strong><span style="font-size: 11pt;"> to build and measure the ML systems that power these programs. This role is focused on machine learning, experimentation, and production measurement. You’ll train models, evaluate performance, design A/B tests, and work with engineering and business stakeholders to improve real-world outcomes.</span></p> <p>&nbsp;</p> <p><span style="font-size: 11pt;">This is a high-impact opportunity to apply ML and experimentation skills to systems that influence real member outcomes at scale. You’ll work on practical, production-facing problems with clear business value, strong cross-functional visibility, and room to help shape how Everlywell uses both ML and AI in operational </span><a rel="noopener noreferrer" href="http://workflows.If" style="font-size: 11pt;" class="postings-link">workflows.If</a><span style="font-size: 11pt;"> you’re excited by hands-on modeling, rigorous experimentation, and building systems that improve decisions in the real world, we’d love to hear from you.</span></p> <p>&nbsp;</p> <p>&nbsp;</p> <p>&nbsp;</p>\n<p></p><p><br></p><b>Responsibilities</b><ul> <li>Build and improve ML models used in engagement and operational workflows</li> <li>Develop models for prediction, prioritization, uplift, and related decisioning use cases</li> <li>Define and monitor model performance, business impact, and system health</li> <li>Design and analyze A/B tests and other measurement approaches to evaluate incremental impact</li> <li>Partner with stakeholders to define success metrics and turn findings into decisions</li> <li>Support production rollout and ongoing monitoring with engineering teams</li> <li>Help evaluate AI- and LLM-powered workflows used in production settings</li> </ul> <div>&nbsp;</div><p><br></p><b>Skills &amp; Abilities Required:</b><ul> <li>5+ years in Applied Science, Data Science, ML, Decision Science, or similar roles</li> <li>Strong hands-on experience training, evaluating, and improving ML models</li> <li>Strong experience designing and analyzing A/B tests</li> <li>Strong Python and SQL skills</li> <li>Experience measuring model, program, or product performance in production</li> <li>Ability to work cross-functionally and communicate clearly with stakeholders</li> <li>PreferredExperience in experimentation platforms, growth or lifecycle modeling, or ML-driven decision systems</li> <li>Experience with causal inference or uplift modeling</li> <li>Experience with LLMs, AI agents, or automated workflows in production</li> <li>Experience in healthcare or regulated environments</li> <li>Snowflake, Python, dbt, Airflow, model registry systems, GitLab</li> </ul><p><br></p><p></p>\n

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