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With the evolving market landscape, we are building the next generation of forecasting solutions by leveraging Generative AI . If you are eager to expand into new-age skill sets —including Python, prompt engineering, building data pipelines, and designing agentic workflows —this is your opportunity. As a Consultant / Senior Consultant, you will focus on implementing Gen AI-powered forecasting use cases in day-to-day client work. This includes applying AI tools to improve efficiency, accuracy, and insight generation in forecasting processes. 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., 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.
Apply explainable AI (XAI) methodologies to ensure models remain interpretable, compliant, and aligned with regulatory guidelines.
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.
Stay updated on emerging Gen AI tools, techniques, and industry best practices to enhance project execution.
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.,
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