Note: The job is a remote job and is open to candidates in USA. Omada Health is on a mission to bend the curve of chronic disease. They are seeking a Staff Forecasting Data Scientist to lead the technical development and automation of their enrollment forecasting capability, transforming a manual process into a robust forecasting engine that enhances decision-making across the business.
Responsibilities
- Design, build, and automate Omada’s core enrollment forecasting engine for the existing book of business, significantly reducing manual effort and increasing forecast reliability and reproducibility
- Translate commercial planning questions into scalable forecasting solutions, partnering closely with Commercial Operations, Sales, Marketing, and Finance to ensure the models reflect real-world dynamics and are usable in day-to-day decision making
- Establish and own best practices for model development, backtesting, performance monitoring, and alerting for enrollment forecasts, helping Omada move from one-off analyses to a robust, production-grade forecasting capability
- Improve forecast accuracy and responsiveness over time by continuously experimenting with new data sources, features, and modeling techniques, and systematically incorporating learnings from forecast performance
- Act as the primary technical leader for forecasting within the Data organization, providing guidance on tooling, coding standards, and architecture, and mentoring other data scientists who contribute to forecasting projects
- Free Commercial Operations leadership to focus on product-line strategy and new go-to-market motions by taking ownership of the technical implementation of base forecasting, while collaborating closely on the assumption framework and narrative
Skills
- 8+ years of experience in data science or applied statistics roles, with at least 3 years focused on forecasting, time series modeling, or revenue/enrollment prediction in a SaaS, healthcare, or similar recurring-revenue business
- Deep hands-on proficiency in Python (e.g., pandas, numpy, scikit-learn, statsmodels, Prophet or similar libraries) and SQL, with a track record of taking models from discovery through deployment and ongoing monitoring
- Strong grounding in statistical and machine learning methods for forecasting (e.g. hierarchical or panel forecasting, gradient boosting, generalized linear models), and a practical sense for when simple models outperform complex ones
- Experience designing and maintaining production data science systems in partnership with data engineering and platform teams, including versioning, backtesting, performance monitoring, and alerting
- Comfort working with messy, real-world commercial data (CRM, marketing, product/event, and financial data) and building robust pipelines and features that can support recurring forecast runs
- 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
- Proven experience influencing cross-functional partners (e.g., Commercial Operations, Sales, Marketing, Finance) using data-driven insights, including framing uncertainty, risk, and scenario ranges in an executive-friendly way
- High degree of ownership and bias toward action: willing to dive into data, prototypes, and code while also stepping back to design scalable systems and long-term improvements to forecasting capabilities
- Comfortable working in a fast‑changing environment where GTM motions, products, and partner needs evolve quickly, and where you help drive clarity through structure, process, and analytics
- Experience implementing or upgrading forecasting tools, analytical workflows, or data models in a high‑growth, evolving, or public‑company environment
- Background in healthcare, digital health, health plans/PBMs, or other complex, regulated industries with multi‑stakeholder sales cycles
- Prior work supporting capacity planning or operational forecasting alongside care delivery, supply chain, or customer support teams
- Familiarity with Salesforce data models and RevOps processes (pipeline management, incentive compensation, territory / quota design)
- Passion for leveraging data, analytics, and emerging technologies (e.g., advanced BI, AI‑driven forecasting) to improve healthcare and outcomes for people living with chronic conditions
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
Company Overview
Company H1B Sponsorship