Principal, Volume Forecasting

GeneDx (Nasdaq: WGS) delivers personalized and actionable health insights to inform diagnosis, direct treatment, and improve drug discovery. The company is uniquely positioned to accelerate the use of genomic and large-scale clinical information to enable precision medicine as the standard of care. GeneDx is at the forefront of transforming healthcare through its industry-leading exome and genome testing and interpretation services, fueled by the world’s largest, rare disease data sets. For more information, please visit www.genedx.com.

Summary

We are seeking a Principal, Volume Forecasting to own and advance GeneDx's end-to-end forecasting capability. This is a senior individual contributor role with high autonomy and broad cross-functional influence. You will build rigorous, data-driven models, drive full adoption of AI and automation tooling, lead forecasting cycles, and deliver the insights that shape strategic decisions across our diagnostics business — all with minimal leadership support in a fast-paced, high-growth organization.

Job Responsibilities

• Own the design, build, and continuous improvement of driver-based volume forecast models integrating historical trends, pipeline data, seasonality, payer/channel mix, and market intelligence across all product lines, architected to scale with new market entries and test launches
• Select and apply appropriate statistical and machine learning forecasting methodologies (e.g., ARIMA, exponential smoothing, regression, ensemble/ML methods) based on data characteristics, forecast horizon, and business context
• Drive full adoption of AI and automation across the forecasting scope, from data ingestion and feature engineering through model training, validation, and reporting, and replace manual processes with scalable, reproducible pipelines
• Lead monthly, quarterly, and annual forecasting cycles end-to-end, coordinating inputs from Sales, Marketing, Operations, and Finance to ensure alignment and accuracy
• Deliver objective forecasting scorecards tracking volume targets, forecast accuracy and variance; lead root-cause analysis in updates to Commercial, Operations, and Finance
• Produce and maintain a rolling volume forecast for incoming test volumes, delivered to the Supply Chain team on a defined cadence to enable downstream inventory planning and operational readiness
• Conduct scenario planning and sensitivity analyses to assess the impact of market changes, new product launches, pricing actions, and strategic initiatives on demand forecasts
• Partner with Commercial, Revenue, and Strategic Finance leaders to provide volume inputs for revenue forecasts, long-range plans, and board-level materials; support market sizing for new testing services
• Design and maintain high-visibility forecasting dashboards and automated reporting, ensuring stakeholders have self-service access to current forecasts, accuracy metrics, and variance tracking
• Serve as the organizational authority on volume forecasting methodology, data quality, and accuracy standards; present methodology choices and results to executive audiences 

Education, Experience, and Skills

• Bachelor's degree in Statistics, Mathematics, Engineering, Economics, Finance, or a quantitative field; Master's degree preferred
• 8–12+ years of experience in Forecasting, Demand Planning, Analytics, or quantitative Consulting within diagnostics, healthcare, biotech, life sciences, or a comparably data-intensive industry
• Deep expertise in statistical forecasting techniques (e.g., ARIMA/SARIMA, exponential smoothing, time-series decomposition, regression) and practical experience applying machine learning methods (e.g., gradient boosting, random forests) to demand forecasting
• Proficiency in Python or R for model development and automation; ability to build production-quality, repeatable forecasting pipelines
• Proficiency in SQL and experience with cloud data platforms (e.g., Snowflake, BigQuery, Redshift); hands-on experience with Tableau or Power BI for dashboard design and automated reporting
• Experience with modern AI/ML forecasting tools and platforms (e.g., Prophet, statsmodels, scikit-learn, DataRobot, or equivalent); track record of driving AI adoption to improve forecast accuracy and efficiency
• Proven track record building driver-based and segment-level forecasts