Sr. Manager/ Associate Director - Forecasting (Pharma)

Tiger Analytics is at the forefront of leveraging AI and advanced analytics to tackle some of the most complex challenges faced by global organizations. We build tailored, data-driven solutions for several Fortune 100 companies, with a strong presence across the US, UK, India, Singapore, and a globally distributed remote team.

We are currently seeking a Data Professional with a strong foundation in data analytics and hands-on experience in demand forecasting and resource allocation within the pharmaceutical and life sciences sector. The ideal candidate will also possess robust coding skills and a practical understanding of how analytics can drive strategic decisions in pharma operations

Key Responsibilities:

• Effectively communicate forecasting strategies and methodologies to cross-functional stakeholders, ensuring alignment with business objectives across teams.
• Promote a culture of data-driven decision-making, educating stakeholders on the how and why behind demand forecasts, scenario planning, and probabilistic modeling to drive adoption and trust.
• Led the development and implementation of advanced forecasting models, collaborating with data engineers, therapeutic area leads, supply planners, and commercial analytics teams to ensure solutions were practical, integrated, and impactful.
• Design and deploy scalable, transparent, and dynamic forecasting models that can adapt to changes in market dynamics, regulatory shifts, or product life cycle stages.
• Foster a collaborative learning environment by mentoring junior analysts and engaging with other data scientists to continuously evolve best practices in pharmaceutical forecasting.
• Engage with external communities and industry conferences to stay current on innovations in statistical and time-series modeling, causal inference, and AI/ML applications in pharma.
• Respond to regulatory and investor demands with innovative forecasting solutions that provide clarity, defensibility, and foresight using cutting-edge analytics tools and statistical techniques.

• Graduate degree in Business Analytics, MBA, or equivalent work experience in a relevant quantitative field
• 10–16 years of professional experience, with at least 7 years in data analytics and forecasting in the pharma/life sciences domain
• Strong expertise in time-series forecasting, including seasonality adjustments and use of exogenous variables (e.g., macroeconomic and marketing data)
• Hands-on experience working with pharmaceutical data sources such as Veeva, IQVIA (PlanTrak, LAAD, PE), and RWD sources like TriNetX, Flatiron, Optum, and Komodo
• Experience applying advanced data science techniques to solve commercial and strategic problems in pharma
• Strong foundation in statistics and econometrics, with practical experience using statistical tools in Python or SAS
• Proven ability to design, build, and scale interpretable forecasting models for both short-term and long-term planning
• Proficiency in data visualization using Tableau, including dashboard development, publishing, and automation
• Strong programming and data manipulation skills in Python and SQL, with the ability to write complex queries
• Excellent communication and stakeholder management skills, with the ability to translate analytics into actionable business insights.

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.