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About This Role
Omada Health is on a mission to bend the curve of chronic disease.
Job overview:
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Reporting to Omada's Senior Director, Clinical \& Translational Research, the Senior Clinical Research Scientist is part of the Clinical \& Translational Research team. This role is responsible for conceptualizing research questions and study designs; analyzing and interpreting data from multiple sources, including internal member\-level data, external EHR data, healthcare claims, survey data, and clinical trial databases; and communicating results through peer\-reviewed manuscripts, abstracts, white papers, value dossiers, and other internal and external reports.
This role will also serve as a key scientific partner in generating clinical, economic, and health outcomes evidence that demonstrates the value of Omada's programs to members, customers, and other external stakeholders. In addition to core clinical and translational research responsibilities, this role will have a strong focus on health economics and outcomes research (HEOR), including cost\-effectiveness, budget impact, utilization, and return on investment analyses to support product strategy, customer value propositions, and commercial growth.
Your impact:
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- Design and conduct studies and analyses to generate high\-quality evidence for Omada's programs by writing detailed evaluation plans and statistical analysis plans, performing advanced statistical analyses, and interpreting and summarizing results.
- Design studies that incorporate mixed methods, integrating quantitative and qualitative data to assess clinical outcomes, member experience, engagement, and implementation effectiveness.
- Lead or support HEOR analyses, including cost\-effectiveness, cost\-offset, budget impact, utilization, and return on investment studies across Omada's lines of business and condition areas.
- Develop evidence packages that connect clinical outcomes to economic value for health plans, employers, health systems, and other strategic customers.
- Analyze medical and pharmacy claims, EHR, laboratory, biometric, and program engagement data to quantify impact on utilization, total cost of care, quality measures, and member outcomes.
- Partner with Clinical Strategy, Commercial, Product, Finance, and Market Access teams to translate research findings into compelling customer\-facing stories, value narratives, and commercialization assets, establishing recurring cross‑functional forums and decision touchpoints where HEOR insights inform strategy and influence diverse internal and external stakeholders.
- Disseminate findings through peer\-reviewed manuscripts, abstracts, conference presentations, white papers, dossiers, and commercial evidence materials.
- Serve as a representative for the Clinical \& Translational Research team in cross\-functional settings, demonstrating strong scientific judgment and the ability to align evidence generation with organizational priorities.
- Support the broader research program by clearly communicating how study findings advance Omada's strategic goals, scientific leadership, and market differentiation.
- Contribute to studies that assess the clinical effectiveness, real\-world effectiveness, and economic value of digital health behavior change programs for chronic conditions such as diabetes, hypertension, obesity, and musculoskeletal conditions.
- Collaborate with cross\-functional program squads to design experiments and quality improvement initiatives that improve engagement, clinical outcomes, healthcare utilization, and value realization using evidence\-based behavioral science approaches.
- Help shape Omada's HEOR roadmap by identifying priority evidence gaps, study opportunities, and publication strategies that strengthen external credibility and commercial readiness, leading department‑level HEOR and evidence‑generation initiatives in partnership with the Senior Director and cross‑functional leaders.
- Build a culture of transparency and scientific rigor within the Clinical \& Translational Research team by clearly communicating HEOR objectives, evidence priorities, and study findings, and regularly connecting the team's work to Omada's mission and strategic goals.
About you:
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You are passionate about understanding the clinical and economic impact of digital health behavior change programs on preventing and treating chronic disease and improving healthcare delivery. You bring strong scientific rigor, analytic depth, and a clear understanding of how outcomes evidence supports customer adoption, payer credibility, and business growth.
To be successful, you will need:
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- 10\+ years relevant experience with a PhD, DrPH, PharmD, MD, ScD, or equivalent advanced training in health economics, epidemiology, biostatistics, health services research, outcomes research, psychology, public health, data science, or a related field.
- Demonstrated experience designing and executing HEOR, real\-world evidence, or health services research studies.
- Strong subject matter expertise in claims data, health plan quality measures, chronic disease, health behavior, AI fluency and agency and/or healthcare delivery transformation.
- Experience with statistical and analytic software such as SAS, STATA, SQL, R, Python, or equivalent tools.
- Strong SQL skills and the ability to work with large, complex healthcare datasets end to end, from extraction and cleaning through analysis, interpretation, and communication.
- 3\+ years of healthcare analytics experience, including experience with medical and pharmacy claims, EHR data, and other real\-world data sources.
- Experience evaluating healthcare utilization, total cost of care, quality performance, and economic outcomes.
- Familiarity with common HEOR methods such as causal inference, comparative effectiveness research, propensity score methods, difference\-in\-differences, cost analyses, budget impact modeling, and cost\-effectiveness analysis.
- Ability to synthesize complex findings into clear, decision\-oriented insights for scientific, clinical, and commercial audiences.
To stand out:
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- Digital health industry experience
- Experience with Tableau and/or similar BI tool
- Experience working on chronic disease research (e.g., diabetes, hypertension, MSK)
- Passionate about improving health behaviors and reducing the incidence, prevalence, and severity of chronic diseases
- Experience in digital health, virtual care, or chronic condition management.
- Experience building economic models, value frameworks, payer\-facing evidence decks, or other market access materials.
- Experience working on cardiometabolic or chronic disease research, including diabetes, obesity, hypertension, or musculoskeletal conditions.
- Experience publishing HEOR or real\-world evidence studies in peer\-reviewed journals or presenting at relevant scientific meetings.
- Experience using Tableau or similar BI tools to communicate outcomes and economic insights.
- Familiarity with employer, health plan, Medicare Advantage, and risk\-based care use cases for digital health evidence.
- Passion for improving health behaviors and reducing the incidence, prevalence, severity, and cost burden of chronic disease.
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: $165,600 \- $207,000
Zone 2: $158,400 \- $198,000
Zone 3: $144,000 \- $180,000
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.
Salary Context
This $144K-$207K range is below the median for Research Scientist roles in our dataset (median: $195K across 149 roles with salary data).
Role Details
About This Role
Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.
The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.
Across the 4,317 AI roles we're tracking, Research Scientist positions make up 4% of the market. At Omada Health, this role fits into their broader AI and engineering organization.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
What the Work Looks Like
A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
Skills Required
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.
Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Compensation Benchmarks
Research Scientist roles pay a median of $222,200 based on 378 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($175K) sits 21% below the category median. Disclosed range: $144K to $207K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Omada Health AI Hiring
Omada Health has 1 open AI role right now. They're hiring across Research Scientist. Based in Remote, US. Compensation range: $207K - $207K.
Remote Work Context
Remote AI roles pay a median of $180,000 across 1,196 positions. About 15% of all AI roles offer remote work.
Career Path
Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.
From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.
The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.
What to Expect in Interviews
Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.
When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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