# Principal Applied Machine Learning Scientist

**Company**: Omada Health
**Location**: Remote, USA
**Work arrangement**: remote
**Experience**: senior
**Job type**: full-time
**Salary**: $270,480 - $338,100
**Category**: IT
**Industry**: Healthcare

**Apply**: https://job-boards.greenhouse.io/omadahealth/jobs/8052599?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_0af85d83-cbf

## Description

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.

**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.

**Benefits:**

- Competitive salary with generous annual cash bonus

- Equity grants

- 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

## Skills

### Required
- Machine Learning
- Python
- AWS SageMaker
- Time-series modeling
- Longitudinal modeling
- Healthcare prediction
- Recommender systems
- Reinforcement learning
- Causal inference

### Nice to have
- Background in healthcare
- Digital health
- Health plans/PBMs
- Peer-reviewed papers
- Conference presentations
- White papers

---

Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/omadahealth/jobs/8052599?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)