Consultant/Senior Consultant - Forecasting and AI Integration

thought leader and go-to partner

next generation of forecasting solutions

implementing Gen AI-powered forecasting use cases

Forecasting

Responsibilities:

Implementation of Forecasting and Allied AI Solutions

• Execute forecasting tasks by combining pharmaceutical domain knowledge with applied AI and analytics-driven data science techniques to deliver actionable insights.
• Implement pre-defined ML-based forecasting models, market sizing tools, and other AI solutions for commercial strategy, brand planning, and lifecycle management.
• Work on translating given business problems into executable AI/ML workflows using techniques such as time-series forecasting, clustering, classification, and NLP.
• Integrate and analyse primary research, secondary data, and third-party sources (e.g., IQVIA, DRG, RWD) to inform forecasting models and recommendations.
• Perform market analysis leveraging AI-based tools (e.g., LLMs, ML-driven forecasting models) to support competitive intelligence, lifecycle management, and launch strategy activities.
• Collaborate with cross-functional teams (data scientists, engineers, consultants) to ensure solutions are technically sound and aligned with business requirements.
• Maintain and enhance Excel-based and code-based (Python/R) forecasting models, transforming them into client-ready dashboards using tools like Power BI or Tableau.
• Continuously monitor model outputs and implement improvements to enhance accuracy.
• Apply explainable AI (XAI) methodologies to ensure models remain interpretable, compliant, and aligned with regulatory guidelines.

Use Case Delivery

• Support the execution of AI/ML forecasting use cases as defined by senior stakeholders.
• Assist in integrating Gen AI workflows into existing forecasting processes to improve efficiency and scalability.
• Prepare and present outputs, dashboards, and reports for client delivery, ensuring accuracy and clarity.
• Stay updated on emerging Gen AI tools, techniques, and industry best practices to enhance project execution.

Qualifications:

• Bachelor’s in

  Life Sciences, Engineering, Computer Science

  , or related field; Master’s in

  Biotech, Data Science, Business Analytics, or MBA

  preferred.
• Minimum 4-5 years of experience in commercial pharma analytics or consulting, with in hands-on AI/ML application preferred.
• Hands-on experience with forecasting models, data analysis, and reporting tools.
• Strong understanding of pharmaceutical datasets (IQVIA, DRG, RWE, EMR/EHR) and how to integrate them into AI solutions.
• Familiarity with AI/ML concepts, particularly in forecasting applications.
• Experience with Python, R, SQL, Power BI/Tableau, and ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch) will be preferred.
• Strong problem-solving and analytical skills.
• Excellent communication skills and attention to detail.