Associate Director, Forecasting – Systemic Mastocytosis (SM)
Sanofi
August 06, 2026
On-site
Cambridge, MA
$148,500 - $214,500 USD yearly
Operations
Main Responsibilities:
- Lead forecasting for Systemic Mastocytosis (SM) treatments in-line (first AYVAKIT, then pipeline products) and deliver proactive insights on threats/opportunities.
- Collaborate with Commercial and Finance to develop/document patient, volume, and revenue forecasts for annual strategic planning & budgeting, bi-annual medium-term updates, and monthly rolling near-term forecasts.
- Coordinate forecasting deliverables with other therapeutic areas; harmonize across assets and functions.
- Partner with Analytics & Finance on end-of-month closing analyses (price/volume, demand/inventory).
- Provide monthly updates to Commercial leadership integrating latest actuals, analytics, and market inputs.
- Enhance forecast models to reflect brand strategy (e.g., segmentation, patient flow).
- Partner with Market Research on demand/conjoint and other study design for forecast inputs.
- Work with Finance & Market Access on GTN/access assumptions, payer mix analysis, and price/volume waterfalls.
- Pressure-test assumptions using analog/external forecasts; align US deliverables with Global forecasting guidance and aggregation.
- Coordinate with Finance & Demand Planning to deliver appropriate SKU forecasts for supply chain planning.
- Deliver ad-hoc analyses for initiatives/risks; review model inputs with Data/Analytics and external data providers.
- Coach junior team members.
Qualifications:
- Bachelor’s required; MBA/MS/MD/PhD preferred.
- 3+ years in pharma/biotech analytics, forecasting, and/or market research (consulting and/or advanced degrees considered).
- Strong communication/presentation and project management; ability to work in a matrixed environment.
- Knowledge of pharma data sources and payer/health insurance environment.
Preferred Skills:
- Rare Disease/Oncology/Hematology experience.
- Excel-based forecast modeling (design/develop/maintain).
- VBA, SQL, R, Python (or similar).
- Cloud analytics/data warehouses (e.g., Snowflake, Databricks).
- Lead forecasting for Systemic Mastocytosis (SM) treatments in-line (first AYVAKIT, then pipeline products) and deliver proactive insights on threats/opportunities.
- Collaborate with Commercial and Finance to develop/document patient, volume, and revenue forecasts for annual strategic planning & budgeting, bi-annual medium-term updates, and monthly rolling near-term forecasts.
- Coordinate forecasting deliverables with other therapeutic areas; harmonize across assets and functions.
- Partner with Analytics & Finance on end-of-month closing analyses (price/volume, demand/inventory).
- Provide monthly updates to Commercial leadership integrating latest actuals, analytics, and market inputs.
- Enhance forecast models to reflect brand strategy (e.g., segmentation, patient flow).
- Partner with Market Research on demand/conjoint and other study design for forecast inputs.
- Work with Finance & Market Access on GTN/access assumptions, payer mix analysis, and price/volume waterfalls.
- Pressure-test assumptions using analog/external forecasts; align US deliverables with Global forecasting guidance and aggregation.
- Coordinate with Finance & Demand Planning to deliver appropriate SKU forecasts for supply chain planning.
- Deliver ad-hoc analyses for initiatives/risks; review model inputs with Data/Analytics and external data providers.
- Coach junior team members.
Qualifications:
- Bachelor’s required; MBA/MS/MD/PhD preferred.
- 3+ years in pharma/biotech analytics, forecasting, and/or market research (consulting and/or advanced degrees considered).
- Strong communication/presentation and project management; ability to work in a matrixed environment.
- Knowledge of pharma data sources and payer/health insurance environment.
Preferred Skills:
- Rare Disease/Oncology/Hematology experience.
- Excel-based forecast modeling (design/develop/maintain).
- VBA, SQL, R, Python (or similar).
- Cloud analytics/data warehouses (e.g., Snowflake, Databricks).