Associate Director, Business Insights and Analytics- Data Science

MSD•North Wales, PA

3d•Hybrid

About The Position

The Associate Director will partner with the Digital Human Health (DHH) area to use and apply data to produce actionable insights that drive greater customer and market comprehension to inform launch strategies, help meet in-line brand growth objectives, and achieve improved customer engagement. They are an integral part in helping to facilitate the creation of actionable commercial use-cases that create ‘data-driven’ decisions, that leverage knowledge across the organization and are more relevant to the customer. The preferred candidate will have an entrepreneurial spirit, comprehension of healthcare & technology, a demonstrated record of producing actionable insights from analytics. The candidate will need to comprehend the nuances of different product lines and are well versed in the Life Science commercial space. They will have demonstrated consistently strong leadership skills, an ability to work objectively and deal well with ambiguity and strong partnership skills. They will empower a growth mindset and inspire a culture of continual learning. This role will require interfacing and collaborating with many teams requiring strong communication skills. Colleagues who will thrive in this role are motivated by developing a deep appreciation of pharma secondary data sources and possess an ability to define and translate objectives and business questions into analytical problems that require advanced and scalable solutions that produce actionable insights.

Requirements

Understanding of the pharmaceutical commercial analytics and business acumen Expertise: Deep understanding of the unique opportunities and challenges with ability to use analytics to solve business problems.
Analytics Champion: Application of advanced marketing analytics methods to inform customer engagement experience, insight generation, predictive model performance and GenAI agents to inform both operational and Marketing decisions.
Communication and Storytelling: Derive actionable business insights from secondary-data sources and communicate them effectively to business stakeholders.
Decision Making and Critical Thinking: Identify and understand problems and opportunities, analyze quantitative and qualitative information, establish decision criteria, generate and evaluate alternatives, and make timely decisions.
Emotional Intelligence: Build trust, encourage two-way communication, and strengthen relationships. Able to navigate relationships with stakeholders while achieving business results.
Networking and Partnerships: Build and leverage relationships within and across stakeholder groups and within DHH to achieve results.
Complex Data Management: Substantial experience in interpreting complex datasets, particularly patient claims data.
BS (or equivalent) in Data Science, Mathematics, Economics, Computer Science, Statistics, Decision Science, Marketing, Engineering, or Public Health is required.
3+ years of relevant experience delivering complex analytical projects in the pharmaceutical/biotech/healthcare industry
Knowledge in mining patient medical claims/EMR data with a strategic mindset and proven record of being able to produce actionable business insights that drive positive commercial results.
Knowledge in developing both machine learning and descriptive algorithms/modeling using such languages as Python, R studio, SAS, SQL etc.
Knowledge in development of AI/GenAI models, data pipelines as well as agent development and orchestration
Self-motived, proactive mindset, and ability to work independently
Effective interpersonal and communication skills
Strong business acumen, with proven ability to comprehend business processes and commercial strategies in detail and translate these into detailed business standards/questions that power analytics.
Effective stakeholder management and communication skills, along with the ability to convey appropriately and confidently with colleagues from different backgrounds and seniority levels
Effective organizational and project management skills to work effectively across organization and manage capability of team of data scientists efficiently and effectively
Proven data science leveraging advanced statistical methods, Machine Learning/Artificial Intelligence, Natural Language Processing (NLP) modeling and model evaluation is a plus.

Nice To Haves

MBA, MS or PhD degree is preferred.
Preferred: Prior hands-on experience working with healthcare data especially in EMR/EHR, Claims Data and various IQVIA /KOMODO data offerings

Responsibilities

Leadership and Mentorship: Lead a team of business analysts, providing guidance on best practices in data analytics, data visualization and storytelling with data.
Lead and Innovate: Engage with BU leaders across the US commercial and DHH organization to prioritize and enhance customer engagement solutions, ultimately delivering on business performance.
Expertise in Data, Analytics & AI: Serve as a subject matter expert in predictive models & prescriptive analytics, and GenAI/AI models, as well as agentic frameworks and as trusted advisor to inform commercial customer engagement decisions.
Optimize: Drive the implementation of new analytics and AI methodologies to optimize resource management decisions for the brand and in support of the larger portfolio.
Business Translation: Translate complex business needs and priorities into analytical plans, providing actionable insights and effectively communicating advanced analytics to inform business decisions.
Collaboration: Work closely with DHH colleagues (i.e., data visualization, data solutions) and Marketing stakeholders to deliver best-in-class solutions and data-driven insights.
Project Management. Manage analytics and digital solutions projects to deliver actionable and meaningful insights to marketing stakeholders in a timely manner.
Staying Abreast with Industry Trends: Stay current with industry trends and advancements in analytical methodologies to enhance organizational analytic capabilities.
Innovation and Experimentation with Agile Mindset in Mind: Contribute to innovative experimentations, focusing on idea generation, incubation, and using tangible, measurable criteria to make incremental meaningful improvements to the business processes and strategies using data.