Experience: 10+ years in Pharma, Life Sciences, Commercial Analytics, Forecasting, Data Architecture, and Product Management.
Job Summary
We are seeking an experienced Enterprise Forecasting Architect to lead the design and implementation of next-generation, GenAI-powered forecasting and analytics platforms for the Life Sciences and Pharmaceutical industry. The ideal candidate will possess deep expertise in commercial forecasting, data engineering, cloud-based analytics, and modern product management.
This role goes beyond traditional data architecture; you will act as a bridge between technical execution and business value. By partnering with Commercial Operations, Market Access, Finance, and Data Engineering, you will build scalable, mobile-enabled, and user-centric forecasting platforms that integrate AI/ML and NLP to support executive strategic decision-making and S&OP processes.
Key Responsibilities
Architecture & Data Engineering
Design and implement end-to-end forecasting architecture and unified data products for pharmaceutical products across launch, growth, and mature brands.
Partner with Data Engineering teams to build scalable, resilient data pipelines on cloud platforms (AWS, Azure, or Google Cloud Platform).
Design advanced data models that seamlessly integrate multiple complex data sources, including IQVIA, Symphony Health, Claims, EMR/EHR, Specialty Pharmacy, Competitive Intelligence, and CRM (Veeva, Salesforce).
Forecasting & Domain Expertise
Develop robust demand, patient-based, epidemiology-based, sales, and revenue forecasting models.
Integrate Sales and Operations Planning (S&OP) processes directly with commercial forecasting platforms to ensure supply chain and commercial alignment.
Drive advanced domain analytics, including Omnichannel Analytics, Patient Journey Analytics, Digital Marketing Analytics, and Launch Excellence/Brand Performance metrics.
Perform sensitivity analysis, market simulations, and what-if scenario modeling.
GenAI, Product Management & UX
Lead the integration of GenAI-powered features into enterprise contexts, including NLP interfaces and automated narrative generation to translate complex data into actionable insights.
Apply strong Product Management and UX capabilities to ensure the output is a highly usable, intuitive data product, rather than just a "data dump."
Design and deploy mobile-enabled analytics and executive decision dashboards.
Leadership & Delivery
Establish strict forecasting governance, assumptions management, and scenario planning processes.
Operate within an Agile delivery methodology, demonstrating the ability to iterate quickly in a complex, cross-functional stakeholder environment.
Ensure compliance with Pharma industry regulations and data governance standards.
Mentor analysts, data scientists, and engineering teams on best practices for data product delivery.
Required Qualifications
Bachelor s or Master s degree in Data Science, Statistics, Economics, Life Sciences, Computer Science, or a related field.
10+ years of proven experience delivering commercial forecasting, data engineering, and analytics platforms in the biopharma or life sciences industry.
Strong understanding of various forecasting methodologies: Patient-based, Demand, Revenue, Market Sizing, and Opportunity Assessment.
Demonstrated experience building and deploying GenAI-powered features (LLMs, NLP) in enterprise workflows.
Strong Product Management mindset with a proven track record of designing user-centric data products and executive dashboards.
Expertise in the modern data stack: AWS Cloud Services, Python, SQL, PySpark, Databricks, Snowflake, and Tableau/Power BI.
Deep knowledge of pharmaceutical data assets (IQVIA, Symphony, Claims, SP, Market Research).
Proven ability to operate iteratively in an Agile framework and manage complex stakeholder relationships.
Preferred Qualifications
Prior experience within Genentech, Roche, or a comparable top-10 biopharma commercial analytics environment.
Familiarity with internal Genentech data platforms such as Oasis, IRIS, GPS (or equivalents at comparable organizations).
Broad therapeutic area forecasting experience (e.g., Oncology, Immunology, Rare Disease, Specialty Therapeutics).
Experience with Veeva CRM and Commercial Data Warehouses.
AWS Solution Architect or Data Analytics certifications.
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