In this role, you will work with McKinsey colleagues and clients on Life Sciences analytics topics, including analytics on licensed third-party and proprietary data, as well as leveraging external and McKinsey-developed Generative AI tools.
You may act as a translator, shaping business questions into analytical methodologies and Generative AI prompts, as well as an executor of these analyses. These projects will mostly leverage analytics for client projects in pharma commercial topics, but may span the scope of the Life Sciences industry including medical devices, and non-commercial pharma topics.
You will be working with McKinsey colleagues to scope business questions and understand, disaggregate, and prioritize their information needs in client engagements. You will problem solve across various international, cross-functional knowledge & intelligence teams to determine the most appropriate solutions to key issues, effectively balancing quality, availability, timelines, and cost factors.
You will leverage proprietary and third-party data and tools (analytical, industry-specific, and function-specific) to perform primary research and required analyses with the highest rigor. You will also perform analytical analyses on various third-party and proprietary data, leveraging a variety of analytical approaches and tools (e.g., Excel, R, Generative AI tools). You will then communicate insights and deliver end products to consulting teams in a variety of formats, including memos, PowerPoint presentations and tables.
In addition to working with consulting teams and clients, you will continuously develop your knowledge and skills in Life Sciences. Together with LSi colleagues and Life Sciences practice leadership, you will analyze new topics and trends and integrate them into our existing capabilities infrastructure, or potentially develop new offerings.
You can expect extensive coaching and further development opportunities. In addition to mentoring from experienced colleagues, you will regularly take part in high-quality internal training.