Data Professional Opportunity

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.
• Lead 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.