Associate Principal/Principal - Forecasting & AI Integration

PharmaACE has been a thought leader and go-to partner for major pharmaceutical companies, supporting their commercial forecasting needs for over two decades. Our deep expertise spans Forecasting, Business Analytics, Competitive Intelligence, Sales Analytics , and operating through an Analytics Centre of Excellence model.

With the evolving market landscape, we are building the next generation of forecasting solutions by leveraging Generative AI . If youve mastered traditional forecasting models and are eager to expand into new-age skill sets including Python, prompt engineering, building data pipelines, and designing agentic workflows this is your opportunity.

Lets work together to make Forecasting truly ForecAstIng

Responsibilities:

Development and Implementation of Forecasting AI Solution:

• Lead end-to-end delivery of applied AI and analytics driven forecasting projects, combining pharmaceutical domain knowledge with advanced data science techniques to deliver actionable insights.
• Drive design and implementation of ML-based forecasting models, market sizing tools, and other AI solutions for commercial strategy, brand planning, and lifecycle management.
• Translate business challenges into AI/ML use cases and oversee development and deployment of appropriate models (e.g., time-series, clustering, classification, NLP).
• Integrate and analyze primary research, secondary data, and third-party sources (e.g., IQVIA, DRG, RWD) to inform strategic recommendations.
• Conduct robust market analysis leveraging AI-based tools (e.g., LLMs, ML-based forecasting models) to provide competitive intelligence and recommendations on brand planning, lifecycle management, and launch strategies.
• Collaborate with cross-functional teams (data scientists, engineers, consultants) to ensure technical robustness and business relevance of all solutions.
• Develop and refine Excel-based and code-based (Python/R) forecasting models and transform them into client-facing tools and dashboards using platforms like Power BI or Tableau.
• Continuously monitor and increase the accuracy of the forecast models
• Leverage XAI (explainable AI) methodologies to ensure models are interpretable, trustworthy, and aligned with client regulatory frameworks.

Leadership:

• Act as the primary client contact for key AI/analytics engagements, ensuring alignment between project deliverables and strategic business needs.
• Facilitate client workshops, deliver strategic recommendations, and manage expectations across multiple stakeholders.
• Present AI-enabled insights and model outputs through compelling narratives and data visualizations tailored for business leaders.
• Stay up to date with the new technological advancement in the forecasting space and being a thought partner for our clients to drive innovative solution in their respective organization
• Develop deep client relationships to identify follow-on opportunities and contribute to account growth.

Team Leadership & Capability Building

• Manage and mentor teams of Consultants, Senior Consultants, and Analysts, guiding technical execution and business storytelling.
• Contribute to the development of internal AI/analytics capabilities by codifying best practices, creating reusable frameworks, and enabling knowledge sharing.
• Support the training and development of junior team members on AI/ML tools, pharma analytics, and client engagement.
• Promote a learning culture that embraces innovation, experimentation, and continuous improvement.

Qualifications:

• Bachelors in Life Sciences, Engineering, Computer Science , or related field; Masters in Biotech, Data Science, Business Analytics, or MBA preferred.
• Minimum 12 years of experience in commercial pharma analytics or consulting, with at least 35 years in hands-on AI/ML application.
• Proven track record of managing client engagements and delivering analytics or AI-based solutions in the life sciences domain.
• Experience with Python, R, SQL, Power BI/Tableau, and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch) will be preferred.
• Strong understanding of pharmaceutical datasets (IQVIA, DRG, RWE, EMR/EHR) and how to integrate them into AI solutions.
• Experience with global pharma markets (US/EU) highly desirable.

Other Competencies:

• Strategic thinking with a strong grasp of both technical and business perspectives.
• Excellent communication, presentation, and client management skills.
• Proactive leadership and team management experience in cross-functional environments.
• High attention to detail, a structured approach to problem-solving, and a customer-first mindset.
• Entrepreneurial drive and an innovative, collaborative attitude.