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Omada Health

Principal Applied Machine Learning Scientist

Reposted 25 Days Ago
Be an Early Applicant
Remote
Hiring Remotely in USA
259K-338K Annually
Expert/Leader
Remote
Hiring Remotely in USA
259K-338K Annually
Expert/Leader
Lead research and development of longitudinal health trajectory models and next-best-action decision algorithms. Translate member data into deployable, clinically meaningful models, set evaluation standards, mentor scientists, and collaborate with product, engineering, and clinical teams to productionize and monitor ML solutions that optimize interventions and health outcomes.
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Omada Health is on a mission to bend the curve of chronic disease.

Job overview:

Omada Health is looking for a Principal Applied ML Scientist to lead high-impact research and applied algorithm development focused on predicting where a member is headed next and identifying the intervention most likely to improve outcomes at a specific moment. The role sits at the intersection of machine learning research, causal decisioning, and healthcare product impact, translating longitudinal member data into clinically meaningful and operationally deployable algorithms. This position requires deep technical leadership, strong publication-quality rigor, and the ability to work cross-functionally with product, engineering, and clinical stakeholders.

Your Impact:

Health Trajectory Research

  • Lead research and development of individual- and population-level health trajectory models that predict future member states, risks, and likely progression paths using messy, real-world longitudinal healthcare data.
  • Produce high-quality experimental evidence and technical recommendations that can lead to tangible product features and have a real impact on individual and population health trajectories.

Next Best Action Algorithms

  • Lead the design of next-best-action algorithms that convert predicted trajectories into intervention decisions tailored to a member’s current context and likely future path.
  • Research and apply advanced decision and recommendation policies to safely optimize intervention choice in a healthcare environment.
  • Define objective functions, reward signals, and policy constraints that balance engagement, clinical effectiveness, fairness, and operational feasibility, partnering with product and clinical teams to ensure outputs are actionable and interpretable.

Technical Leadership

  • Serve as the senior scientific lead for algorithmic and evaluation rigor in trajectories and next-best-action, setting standards for problem formulation, evaluation, and publication-quality analysis.
  • Mentor other scientists and data scientists on advanced methods in temporal modeling, reinforcement learning, and causal inference.
  • Collaborate closely with platform, MLOps, and product engineering teams to ensure research outputs can be productionized reliably and monitored appropriately.

About you:

  • Ph.D. in Computer Science, Statistics, Machine Learning, Biostatistics, Applied Mathematics or a related quantitative field is required, will consider a Master’s with substantial, directly related experience at a senior level.
  • Multiple years of post-secondary education experience in machine learning research or applied research science, with a strong record of delivering novel algorithms or high-impact ML systems in production.
  • Deep expertise in time-series or longitudinal modeling, healthcare prediction, recommender systems, reinforcement learning, causal inference, or adjacent research areas relevant to trajectories and next-best-action decisioning.
  • Strong proficiency in Python and modern ML tooling, along with experience deploying models into production environments on cloud platforms such as AWS SageMaker or equivalent.
  • Demonstrated ability to translate ambiguous business questions into well-scoped technical problems, communicate tradeoffs clearly to non-technical stakeholders, and incorporate feedback into model and metric design.

Bonus Points for:

  • Background in healthcare, digital health, health plans/PBMs, or other complex, regulated industries.
  • Peer-reviewed papers, conference presentations or white papers in machine learning, reinforcement learning, causal inference or health AI.

Benefits:

  • Competitive salary with generous annual cash bonus
  • Equity grants
  • Employee stock purchasing plan (ESPP)
  • Remote first work from home culture
  • Flexible Time Off to help you rest, recharge, and connect with loved ones
  • Generous parental leave
  • Health, dental, and vision insurance (and above market employer contributions)
  • 401k retirement savings plan
  • Lifestyle Spending Account (LSA)
  • Mental Health Support Solutions
  • ...and more!

It takes a village to change health care. As we build together toward our mission, we strive to embody the following values in our day-to-day work. We hope these hold meaning for you as well as you consider Omada!

  • Cultivate Trust. We listen closely and we operate with kindness. We provide respectful and candid feedback to each other.
  • Seek Context. We ask to understand and we build connections. We do our research up front to move faster down the road.
  • Act Boldly. We innovate daily to solve problems, improve processes, and find new opportunities for our members and customers.
  • Deliver Results. We reward impact above output. We set a high bar, we’re not afraid to fail, and we take pride in our work.
  • Succeed Together. We prioritize Omada’s progress above team or individual. We have fun as we get stuff done, and we celebrate together. 
  • Remember Why We’re Here. We push through the challenges of changing health care because we know the destination is worth it.

About Omada Health: Omada Health (Nasdaq: OMDA) is reverse engineering the way healthcare is delivered in America, putting the space between doctor visits–where health is won or lost–at the center of care. Today's healthcare system poorly serves chronic conditions that require ongoing support outside of the exam room, like obesity, diabetes, hypertension, cholesterol, and musculoskeletal conditions. Omada’s virtual-first model combines human-led care teams, connected devices, and AI-enabled technology to deliver personalized care at scale, including support for GLP-1 therapy. Omada has served more than two million members since launch across 2,000+ employers, health plans, pharmacy benefit managers, and health systems. Learn more at omadahealth.com.

Omada is thrilled to share that we’ve been certified as a Great Place to Work! Please click here for more information.

We carefully hire the best talent we can find, which means actively seeking diversity of beliefs, backgrounds, education, and ways of thinking. We strive to build an inclusive culture where differences are celebrated and leveraged to inform better design and business decisions. Omada is proud to be an equal opportunity workplace and affirmative action employer. We are committed to equal opportunity regardless of race, color, religion, sex, gender identity, national origin, ancestry, citizenship, age, physical or mental disability, legally protected medical condition, family care status, military or veteran status, marital status, domestic partner status, sexual orientation, or any other basis protected by local, state, or federal laws. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Below is a summary of salary ranges, by geographic zone, for this role*. These ranges represent a good faith estimate of the minimum and maximum base salary for the position in that zone at the time of posting. Please refer to this resource for detail on zone designations.  

Zone 1: $270,480 - $338,100

Zone 2: $258,720 - $323,400

Zone 3: $235,200 - $294,000

Please note that zones may be updated as market data changes but we will honor the range applicable to your zone (which is determined by your location) as of your application date.

*The actual offer, including the compensation package, will be within the posted range for the relevant zone and will be determined based on multiple factors, such as the candidate's skills and experience, and other business considerations such as internal equity.

Please click here for more information on our Candidate Privacy Notice.

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