Home › Companies › Everlywell › Applied Scientist — ML, Experimentation & Decision Systems
Applied Scientist — ML, Experimentation & Decision Systems
Everlywell · Austin, TX · Hybrid · Active · Lever
Job facts
| Field | Value |
|---|---|
| Company | Everlywell |
| Title | Applied Scientist — ML, Experimentation & Decision Systems |
| Normalized title | - |
| Department / team | Technology / Engineering |
| Location | Austin, TX, United States |
| Work model | Hybrid / Hybrid |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Lever |
| Posted / first seen | 2026-03-06 / 2026-05-29 |
| Changed / last seen | 2026-05-29 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Everlywell. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Lever. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in Austin. | Open |
| Department jobs | Active postings in Technology. | Open |
| Work model jobs | Active Hybrid postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Everlywell |
| Source | a2861e73-3940-4c94-8300-a9e1b19f29c8 |
| ATS provider | Lever |
Description
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.
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 2025, an estimated 1 in 94 U.S. adults received an Everlywell test, solidifying our spot as the #1 at-home testing company in the country. 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.
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.
We’re hiring an Applied Scientist 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.
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 workflows.If 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.
Security Notice: Everlywell never requests fees, payment, or banking information at any stage of the recruitment process. Official communications and interview invitations will only come from verified email addresses ending in @everlywell.com or @everlyhealth.com. To ensure your application is secure, always apply directly through our official careers page at https://www.everlywell.com/careers/.
Responsibilities
Build and improve ML models used in engagement and operational workflows
Develop models for prediction, prioritization, uplift, and related decisioning use cases
Define and monitor model performance, business impact, and system health
Design and analyze A/B tests and other measurement approaches to evaluate incremental impact
Partner with stakeholders to define success metrics and turn findings into decisions
Support production rollout and ongoing monitoring with engineering teams
Help evaluate AI- and LLM-powered workflows used in production settings
Skills & Abilities Required:
5+ years in Applied Science, Data Science, ML, Decision Science, or similar roles
Strong hands-on experience training, evaluating, and improving ML models
Strong experience designing and analyzing A/B tests
Strong Python and SQL skills
Experience measuring model, program, or product performance in production
Ability to work cross-functionally and communicate clearly with stakeholders
PreferredExperience in experimentation platforms, growth or lifecycle modeling, or ML-driven decision systems
Experience with causal inference or uplift modeling
Experience with LLMs, AI agents, or automated workflows in production
Experience in healthcare or regulated environments
Snowflake, Python, dbt, Airflow, model registry systems, GitLab
Full job record
| Job ID | 0ac80df7c3e6e31f5750e8adf62ee39730bb2518 |
| Org ID | e9dd650a-24c7-475e-903c-c1eefe2fbf94 |
| Source ID | a2861e73-3940-4c94-8300-a9e1b19f29c8 |
| Board ID | a2861e73-3940-4c94-8300-a9e1b19f29c8 |
| Provider | lever |
| Provider Job Key | 948104c7-330a-4674-b1a3-2d5b57d43b1e |
| Title | Applied Scientist — ML, Experimentation & Decision Systems |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | Austin, TX |
| Department | Technology |
| Team | Engineering |
| Employment Type | Full-Time |
| Workplace Type | hybrid |
| Remote Policy | hybrid |
| Country | United States |
| Region | TX |
| City | Austin |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://jobs.lever.co/everlywell/948104c7-330a-4674-b1a3-2d5b57d43b1e |
| Apply URL | https://jobs.lever.co/everlywell/948104c7-330a-4674-b1a3-2d5b57d43b1e/apply |
| First Seen At | 2026-05-29 07:01:32Z |
| Last Seen At | 2026-06-06 07:57:01Z |
| Last Checked At | 2026-06-06 07:57:01Z |
| Last Changed At | 2026-05-29 07:01:32Z |
| Inactive At | — |
| Source Posted At | 2026-03-06 21:02:45Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=lever/board=everlywell/date=2026-06-06/2026-06-06T07-57-01-417Z-2b2dabd0a567121f82054eedfc2dc95977af50a3cf117e875d243b383467a7e2.json |
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