[Remote] Staff Forecasting Data Scientist

Note: The job is a remote job and is open to candidates in USA. Omada Health is on a mission to inspire and engage people in lifelong health, and they are seeking a Staff Forecasting Data Scientist to lead the technical development and automation of their enrollment forecasting capability. This role involves building and scaling forecasting models to improve forecast quality and support critical planning and 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

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