Senior Manager, Innovation & Digital Health Analytics

Working with Us
Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams rich in diversity. Take your career farther than you thought possible.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us.

Innovation & Digital Health Analytics (IDHA) frequently leads key initiatives in strategic, operational and analytic domains, many of which are highly visible, cross functional, complex (multiple work streams), with significant investment, and innovative in nature.

The IDHA team partners with Drug Development leadership and team to design and deliver innovative analytics solutions to drive data driven decision making that drive trial and portfolio performance. Our diverse analytics team of knowledge management experts, data scientists, analysts and data visualization specialists works on multiple projects simultaneously, ranging from piloting new capabilities, to developing cutting-edge approaches, to operationalizing complex solutions.

In support of Drug Development strategy the Senior Manager, Innovation & Digital Health Analytics partners with Drug Development leadership and BIA Business Partners to pioneer new analytics solutions, improved ways of applying data and analytics to drive value, and cutting edge modeling capabilities related to clinical trials and drug development portfolio, to drive competitive advantage, operational excellence and data driven decisions.

Key Responsibilities and Major Duties
 

• Hands-on analyst that will be expected to design, develop, model and deploy advanced solutions
• Hands-on data munging, statistical modeling and data visualization to pioneer innovative solutions
• Test and build analytics solutions for Drug Development to enable better understanding of trial design and operational feasibility, predicted performance and prescriptive risk mitigation strategies
• Employs disruptive thinking to pressure test trial design, asset plans, and existing trial execution processes
• Uses a sound understanding of analytics techniques and technology and business process to build practical analytics solutions for value capture
• Engage and collaborate with a diverse team of business stakeholders, analysts, data scientists and IT to translate unstructured, complex business problems into data and information needs and deliver the appropriate data, modeling, and/or analytical solutions
• Develop data visualizations and/or dashboards in Tableau or tool-of-preference to facilitate metrics reporting & monitoring, insights consumption, and additional analyses
• Effectively translate the analytics model into business language to ensure insights are understood and acted upon by stakeholders
• Partners with the broader Drug Development Innovation, Business Partner and Data Science teams to identify new opportunities to apply analytics and enhance existing solutions

Qualifications/Degree/Certification/Licensure

• BA/BS required (engineering or quantitative area of study preferred)
• Additional graduate degree preferred (computer science or data science preferred)
• A minimum of 3 years of hands-on analytics experience
• Demonstrated competence in data & analytics skillsets such as data mining, data visualization, machine learning, code development in python/R, Git, cloud computing platforms like AWS, model governance with MLFlow or equivalent
• Experience building data access and visualization tools
• Knowledge of classical machine learning models (Classification, Regression, Clustering, Time-Series Analysis, Dimensionality Reduction etc.)
• Experience writing quality, well-documented and well-tested code
• Familiarity with modern computer vision, computational linguistic and/or transformer-based natural language processing (NLP), Natural Language Generation (NLG), Large Language Models (LLM) frameworks a plus
• Familiarity with MLOps or other method for monitoring model performance a plus

Skills for Success<