Data Analyst I, Field Effectiveness & Alignment

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. 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 .

Data Analyst I -Field Effectiveness

Summary

The Data Analyst I-Field Force Effectiveness & Alignment will play a pivotal role in supporting the commercial strategy and operations of the Field Force Effectiveness (FFE) team. This position is responsible for developing assessments of field performance, driving territory alignment and structuring, optimizing workload distribution across territories and healthcare professionals (HCPs), and providing detailed, actionable insights based on execution analysis to senior leadership and key stakeholders. The ideal candidate will demonstrate hands-on experience in commercial analytics, territory management, workload analysis, and be proficient with key alignment tools (e.g., JTD tool), Veeva CRM, and advanced analytics platforms. Exposure to SQL, Python, AWS, and machine learning is highly valued

Roles & Responsibilities

• Lead and execute territory alignment and structuring projects, implementing changes based on performance, workload analysis, and evolving business needs.
• Assess field force engagement and effectiveness using call activity, IQVIA sales, and Rx datasets, delivering actionable insights to optimize field strategy.
• Perform statistical analysis, data mining, and predictive modelling on large datasets to uncover trends and correlations that support commercial and field team success.
• Collaborate with cross-functional partners (Commercial, Analytics, IT, Operations) to ensure accurate data flow, deliverables, and seamless territory implementation.
• Champion innovation in process efficiency, including automation, advanced data visualization, and integration with AI / ML tools.
• Prepare and present concise analyses, dashboards, and territory action plans for leadership, clearly communicating outcomes and improvement opportunities.
• Utilize and maintain field alignment platforms (e.g., JTD tool) and Veeva CRM for precise territory mapping and data integrity.
• Foster a culture of analytical excellence, knowledge sharing, and continuous learning within the FFE team, integrating feedback and best practices.

Skills and competencies

Experience

If you come across a role that intrigues you but doesn't perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.

Uniquely Interesting Work, Life-changing Careers

With a single vision as inspiring as Transforming patients' lives through science™ , every BMS employee plays an integral role in work that goes far beyond ordinary. Each of us is empowered to apply our individual talents and unique perspectives in a supportive culture, promoting global participation in clinical trials, while our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues.

On-site Protocol

Responsibilities

BMS has an occupancy structure that determines where an employee is required to conduct their work. This structure includes site-essential, site-by-design, field-based and remote-by-design jobs. The occupancy type that you are assigned is determined by the nature and responsibilities of your role :

Site-essential roles require 100% of shifts onsite at your assigned facility. Site-by-design roles may be eligible for a hybrid work model with at least 50% onsite at your assigned facility. For these roles, onsite presence is considered an essential job function and is critical to collaboration, innovation, productivity, and a positive Company culture. For field-based and remote-by-design roles the ability to physically travel to visit customers, patients or business partners and to attend meetings on behalf of BMS as directed is an essential job function.

BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations / adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation / adjustment prior to accepting a job offer. If you require reasonable accommodations / adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to [HIDDEN TEXT] . Visit careers.bms.com / eeo -accessibility to access our complete Equal Employment Opportunity statement.

BMS cares about your well-being and the well-being of our staff, customers, patients, and communities. As a result, the Company strongly recommends that all employees be fully vaccinated for Covid-19 and keep up to date with Covid-19 boosters.

BMS will consider for employment qualified applicants with arrest and conviction records, pursuant to applicable laws in your area.

If you live in or expect to work from Los Angeles County if hired for this position, please visit this page for important additional information : https : / / careers.bms.com / california-residents /

Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations.

Skills Required

Statistical Analysis, Tableau, Veeva Crm, Data Mining, Sql, Powerbi, Vba, Machine Learning, Predictive Modeling, Excel, Python