Associate Principal/Principal - Forecasting & AI Integration

12 years

0 Lacs

Posted:1 week ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

thought leader and go-to partner


next generation of forecasting solutions


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:

  • Bachelor’s in

    Life Sciences, Engineering, Computer Science

    , or related field; Master’s in

    Biotech, Data Science, Business Analytics, or MBA

    preferred.
  • Minimum 12 years of experience in commercial pharma analytics or consulting, with at least 3–5 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.

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