Join EY's Global Delivery Services as a Pharma Forecasting Specialist, a pivotal role driving global, country, and regional forecasting initiatives. This position offers a dynamic environment to leverage your expertise in pharmaceutical forecasting and contribute to strategic decision-making within a leading professional services organization.

As part of EY's commitment to building a better working world, you'll collaborate with diverse, globally connected teams, shaping the future of the pharmaceutical industry. We empower our professionals with future-focused skills and world-class experiences, fostering a culture of continuous learning and development.

Develop comprehensive brand volume forecasts for short-term and long-term strategic planning. Conduct in-depth franchise forecasting, offering insights and recommendations. Address regional and brand-level analytical challenges using quantitative methods. Perform sensitivity analyses to identify opportunities and mitigate risks, thereby improving forecast accuracy.

Collaborate effectively within cross-functional teams, including marketing, finance, and market access, to meet global and regional forecasting needs. Utilize advanced analytical techniques and Python coding to refine and automate forecasting processes. Prepare clear and concise concept notes and presentations to communicate findings to stakeholders and leadership.

A Bachelor's degree in a relevant quantitative field, coupled with 5-8 years of experience in pharmaceutical forecasting and business analysis, is essential. Proficiency in recommendation of assumptions, creation of concept notes, and presentation development is required. Basic Python coding skills are a must.

Key qualifications include strong business analysis skills, knowledge of Long Range Forecasting processes, and excellent communication and stakeholder management abilities. Familiarity with therapeutic areas within the pharma sector is crucial. Experience with tools like SQL, Tableau, or Alteryx, and an understanding of Machine Learning/Statistical Learning are considered advantageous.