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Data

Senior ML Data Scientist - Women’s Health

ŌURA · United States · full-time · Remote

Datafull-timeRemoteUnited StatesUSD 147,900 – 203,000 / yearly
Data Science & AnalyticsSenior
RemoteJobs editorial overview

Strategic Overview

Senior ML Data Scientist - Women’s Health at ŌURA is defined by the responsibilities and candidate requirements in the employer's listing.

The published role emphasizes work such as Contribute to the development and deployment of advanced machine learning pipelines and models for innovative Women's Health features, focusing on time-series analysis and robust validation.

The role is listed for United States with a remote working arrangement, giving candidates the practical context needed to assess fit before applying.

Job seeker snapshot

Key information at a glance

Role focusData
LocationUnited States
WorkplaceRemote
Employmentfull-time
Experience3+ years
SalaryUSD 147,900 – 203,000 / yearly
PostedNov 1, 2026
Last seenNov 2, 2026
Role context

About This Role

Our mission at ŌURA is to empower every person to own their inner potential. Our award-winning products help our global community gain a deeper knowledge of their readiness, activity, and sleep quality by using their Oura Ring and its connected app. We've helped millions of people understand and improve their health by providing daily insights and practical steps to inspire healthy lifestyles.

Empowering the world starts with living our values and empowering our team. As a quickly growing company focused on helping people live healthier and happier lives, we ensure that our team members have what they need to do their best work — both in and out of the office.

We are seeking a highly experienced and driven Senior Machine Learning Data Scientist to join our Women's Health team. You will play a pivotal role in developing and commercializing cutting-edge machine learning models and algorithms, leveraging wearable health data to improve women's health outcomes.

What the role delivers

Key Responsibilities & Objectives

  • Contribute to the development and deployment of advanced machine learning pipelines and models for innovative Women's Health features, focusing on time-series analysis and robust validation.
  • Drive the commercialization of machine learning models and algorithms, collaborating closely with cross-functional teams including scientists, product managers, software developers, product designers and test engineers.
  • Design and execute rigorous statistical analyses for model performance evaluation, monitoring, and generating actionable insights to inform strategic product decisions.
  • Conduct in-depth exploratory research to identify and characterize novel health sensing features, translating proof-of-concept ideas into scalable, commercialized products.
  • Contribute to the development of best practices for machine learning within the Women's Health team.
  • Present and communicate complex technical concepts to diverse audiences.
  • This is a remote US role with a preference for candidates based in San Francisco, San Diego, or Boston.
Candidate blueprint

Required Qualifications & Candidate Blueprint

  • PhD in Biomedical Engineering, Electrical Engineering, Biostatistics, Computer Science, or a related field. And 3+ years of industry experience in machine learning and data science.
  • 5+ years of advanced programming experience in Python and SQL.
  • Extensive experience with a wide range of machine learning and statistical modeling techniques, including deep learning, time-series analysis, and signal processing.
  • Demonstrated experience in the full lifecycle of developing and commercializing machine learning models and algorithms.
  • Excellent communication skills, and the ability to articulate complex technical concepts to both technical and non-technical audiences.
  • Self-driven, motivated, have a pragmatic can-do attitude and delivery-focused mindset: you can move quickly and prioritize effectively.
Additional fit signals

Preferred Qualifications

  • Strong domain knowledge in Women's Health and experience with health data from wearables are significant plusses.
Compensation & benefits

Salary & Benefits

Published compensation: USD 147,900 – 203,000 / yearly

  • Competitive salary and equity packages
  • Health, dental, vision insurance, and mental health resources
  • An Ōura Ring of your own plus employee discounts for friends & family
  • 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off
  • Paid sick leave and parental leave
  • ŌURA is proud to be an equal opportunity workplace. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Live market comparison

Salary Benchmark

This role’s published compensation is compared with active employer-disclosed ranges for the same role at the Senior level, in the same currency and pay period.

This jobUSD 147,900 – 203,000 / yearly
Current market range$13,000 – $366,000 · per year
Comparable jobs17

Benchmark uses active employer job postings in our database, excludes this listing, and matches the currency and pay period. It is not a third-party salary estimate; currencies are not converted.

Employer-provided source content

Full Job Description

The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.

Our mission at ŌURA is to empower every person to own their inner potential. Our award-winning products help our global community gain a deeper knowledge of their readiness, activity, and sleep quality by using their Oura Ring and its connected app. We've helped millions of people understand and improve their health by providing daily insights and practical steps to inspire healthy lifestyles.

Empowering the world starts with living our values and empowering our team. As a quickly growing company focused on helping people live healthier and happier lives, we ensure that our team members have what they need to do their best work — both in and out of the office.

We are seeking a highly experienced and driven Senior Machine Learning Data Scientist to join our Women's Health team. You will play a pivotal role in developing and commercializing cutting-edge machine learning models and algorithms, leveraging wearable health data to improve women's health outcomes. You will lead complex projects, mentor junior team members, and contribute significantly to the strategic direction of our technology..

What You Will Do:

  • Contribute to the development and deployment of advanced machine learning pipelines and models for innovative Women's Health features, focusing on time-series analysis and robust validation.
  • Drive the commercialization of machine learning models and algorithms, collaborating closely with cross-functional teams including scientists, product managers, software developers, product designers and test engineers.
  • Design and execute rigorous statistical analyses for model performance evaluation, monitoring, and generating actionable insights to inform strategic product decisions.
  • Conduct in-depth exploratory research to identify and characterize novel health sensing features, translating proof-of-concept ideas into scalable, commercialized products.
  • Contribute to the development of best practices for machine learning within the Women's Health team.
  • Present and communicate complex technical concepts to diverse audiences.
  • This is a remote US role with a preference for candidates based in San Francisco, San Diego, or Boston.

This is a remote US role with a slight preference for candidates based in San Francisco, San Diego, or Boston.

What you'll bring:

  • PhD in Biomedical Engineering, Electrical Engineering, Biostatistics, Computer Science, or a related field. And 3+ years of industry experience in machine learning and data science.
  • 5+ years of advanced programming experience in Python and SQL.
  • Extensive experience with a wide range of machine learning and statistical modeling techniques, including deep learning, time-series analysis, and signal processing.
  • Demonstrated experience in the full lifecycle of developing and commercializing machine learning models and algorithms.
  • Excellent communication skills, and the ability to articulate complex technical concepts to both technical and non-technical audiences.
  • Self-driven, motivated, have a pragmatic can-do attitude and delivery-focused mindset: you can move quickly and prioritize effectively.

Nice to have:

  • Strong domain knowledge in Women's Health and experience with health data from wearables are significant plusses.

Benefits

At Ōura, we care about you and your well-being. Everyone here at Ōura has a ring of their own and we are continually looking to improve employee health.

What we offer:

  • Competitive salary and equity packages
  • Health, dental, vision insurance, and mental health resources
  • An Ōura Ring of your own plus employee discounts for friends & family
  • 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off
  • Paid sick leave and parental leave

Ōura takes a market-based approach to pay, which may vary depending on your location. US locations are categorized into tiers based on a cost of labor index for that geographic area. While most offers will be closer to the starting range, successful candidates' pay will be determined based on job-related skills, experience, qualifications, work location, internal peer equity, and market conditions. These ranges may be modified in the future.

Region 1: $172,550 - $203,000
Region 2: $158,950 - $187,000
Region 3: $147,900 - $174,000

A recruiter can determine your Region based on your US location.

We are not considering candidates residing in the following states: Alaska (AK), Delaware (DE), Iowa (IA), Mississippi (MS), Nebraska (NE), South Dakota (SD), West Virginia (WV), and Wisconsin (WI).

ŌURA is proud to be an equal opportunity workplace. We celebrate diversity and are committed to creating an inclusive environment for all employees. Individuals seeking employment at ŌURA are considered without regard to age, ancestry, color, gender (including pregnancy, childbirth, or related medical conditions), gender identity or expression, genetic information, marital status, medical condition, mental or physical disability, national origin, protected family care or medical leave status, race, religion (including beliefs and practices or the absence thereof), sexual orientation, military or veteran status, or any other characteristic protected by federal, state, or local laws. We will not tolerate discrimination or harassment based on any of these characteristics.

We will work to ensure individuals with disabilities are provided reasonable accommodation to participate in the interview process, to perform essential job functions, and to receive other benefits and privileges of employment.

Disclaimer: Beware of fake job offers!
We’ve been alerted to scammers posing as ŌURA recruiters, especially for remote roles. Please note:

  • Our jobs are listed only on the ŌURA Careers page and trusted job boards.
  • We will never ask for personal information like ID or payment for equipment upfront.
  • Official offers are sent through Docusign after a verbal offer, not via text or email.

Stay cautious and protect your personal details.

To all recruitment agencies: ŌURA does not accept agency resumes. Please do not forward resumes to our jobs alias, ŌURA employees, or any other organization's location. ŌURA is not responsible for any fees related to unsolicited resumes.

RemoteJobs original analysis

Editor’s Market Perspective (Our Custom Analysis)

Why This Position Matters

This opening may suit candidates who can demonstrate experience relevant to the employer's published requirements. Its strongest career signal is the scope of the work itself — particularly Contribute to the development and deployment of advanced machine learning pipelines and models for innovative Women's Health features, focusing on time-series analysis and robust validation. — rather than a generic title alone.

Resume & Application Strategy

For the application, connect specific examples from your experience to the responsibilities and qualifications in the employer's description. Quantify outcomes from comparable work, and place the most relevant evidence near the top of the resume. When the employer explicitly names tools, platforms, leadership scope, or domain experience, use those source terms accurately and in context.

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We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.