Brand Analytics – Data Analyst

You will develop a deep understanding of internal customer data and analytical needs, focusing on customer-facing model leadership. You will champion the use of local customer insight in strategic and resourcing decisions across the business and identify and prioritize enhancements and new analytic capabilities. You should be able to lead the development, deployment, and embedding of such capabilities across the organization while instilling a culture of continuous improvement, testing, and deployment of new capabilities. Developing innovative analytical practices to create and sustain a competitive advantage is expected, as is accessing appropriate information via a variety of tools and sources, and summarizing and presenting findings through various communication channels.

You should be capable of applying deeper technical skills and knowledge that is shared across the functional area, including deep knowledge of key data sets and modeling capabilities. A high level of understanding of the points of integration between your work and that of colleagues is important. Monitoring the external environment to stay current on leading analytic capabilities, both within and outside of pharma, and applying those insights within the organization will also be key.

Essential For The Role

A quantitative bachelor degree from an accredited college or university is required in one of the following or related fields: Engineering, Operations Research, Management Science, Economics, Statistics, Applied Math, Computer Science, or Data Science. An advanced degree (Masters, MBA, or PhD) is preferred. You should have 3+ years of experience applying advanced methods and statistical procedures on large and disparate datasets, along with recent experience and proficiency in PySpark, Python, R, and SQL. Working knowledge of data visualization tools such as Power BI, MicroStrategy, Tableau, QlikView, D3.js, or similar is expected, as well as familiarity with platforms like Databricks and experience with IQVIA data sets. Strong skills in Excel and PowerPoint are required, along with expertise in managing and analyzing a range of large, transactional databases. A background in statistical analysis and modeling is a plus, as is experience with machine learning. You should be able to derive, summarize, and communicate insights from analyses and have strong organization and time management skills.

Desirable

Strong leadership and interpersonal skills are important, with a demonstrated ability to work collaboratively with business leaders and cross-functional partners. You should have excellent communication and influencing skills and the ability to develop and present clear, compelling reviews of independently developed analyses, including insights and business implications. Strategic and critical thinking skills are essential to engage and maintain credibility with the Commercial Leadership Team.