You will be taken to Bristol Myers Squibb’s own careers page to apply. Job ID R1605919.
Job description
At Bristol Myers Squibb, our employees often ask, “Who are you working for?”—a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. This is work that transforms the lives of patients, and the careers of those who do it.
Own day-to-day operations and continuous enhancement of the in-house Sales Crediting Platform, ensuring accurate, timely and reliable processing of sales crediting activities.
Translate business requirements, sales crediting rules and Incentive Compensation processes into technical requirements and implement scalable solutions.
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Develop, maintain and optimize data pipelines, transformations, business rules and validation processes supporting sales crediting.
Monitor platform performance, identify data/process issues, perform root-cause analysis and drive timely resolution of production issues.
Partner with Incentive Compensation stakeholders to understand changes in business rules, field force structures, products, territories and crediting methodologies and translate these into platform enhancements.
Establish robust data quality, validation and reconciliation frameworks to ensure accuracy and completeness of sales crediting outputs.
Support recurring Incentive Compensation cycles and ensure operational readiness, including testing, validation, deployment and post-production monitoring.
Identify opportunities to automate manual processes and improve platform efficiency, scalability and reliability.
Data Engineering & Analytics
Build and maintain scalable data pipelines to ingest, transform, validate and integrate data from multiple internal and external sources.
Work with large and complex datasets using SQL, Python and Databricks to perform data transformation, analysis and troubleshooting.
Develop reusable data processing and analytical solutions that improve efficiency, reduce manual intervention and enhance data quality.
Collaborate with Data & Analytics and IT teams to develop and enhance data architecture, pipelines, analytical tools and platform capabilities.
Perform data profiling, reconciliation, anomaly detection and root-cause analysis across multiple data sources.
Develop dashboards, reports and analytical outputs where required to monitor sales crediting performance, data quality and operational KPIs.
Technology, Automation & AI
Identify and implement opportunities to leverage AI, GenAI, machine learning, automation and emerging technologies to improve Incentive Compensation and sales crediting processes.
Explore practical applications of AI for areas such as data validation, anomaly detection, issue identification, process automation, documentation and operational insights.
Stay current with emerging data engineering, AI and analytics technologies and assess their potential application within the Incentive Compensation ecosystem.
Continuously challenge existing processes and identify opportunities to make the platform more automated, scalable, intelligent and user-friendly.
Stakeholder & Project Management
Partner closely with Incentive Compensation, Commercial, IT, Data & Analytics and other cross-functional stakeholders to understand requirements and deliver solutions.
Communicate complex technical and data concepts clearly to non-technical stakeholders.
Manage multiple enhancements, operational priorities and projects while maintaining high standards of quality and execution.
Lead or contribute to platform enhancement initiatives from requirements gathering through development, testing, deployment and stabilization.
Collaborate with vendor/partner teams where required and ensure effective knowledge transfer and delivery.
Process & Knowledge Management
Develop and maintain process documentation, SOPs, technical documentation, data dictionaries, process maps, business requirements and validation frameworks.
Establish best practices around data engineering, testing, quality control, change management and platform operations.
Build strong domain knowledge of Incentive Compensation, sales crediting, commercial operations and relevant business processes.
Become a subject matter expert on the Sales Crediting Platform and serve as a key point of contact for platform-related questions and issues.
Skills & Competencies Technical / Data Engineering
Strong hands-on experience with SQL and Python.
Strong understanding of data engineering concepts including ETL/ELT, data pipelines, data transformation, data quality, data validation and data integration.
Experience working with Databricks and/or similar cloud-based data platforms.
Experience working with large, complex datasets and multiple data sources.
Understanding of data architecture, data modeling and scalable data processing.
Experience with APIs, cloud technologies, workflow orchestration or CI/CD is a plus.
Experience with BI/visualization tools such as Power BI, Tableau or similar is an advantage.
AI & Emerging Technology
Strong interest in and practical understanding of AI/GenAI and emerging data technologies.
Demonstrated ability to identify opportunities to apply AI or automation to improve business processes.
Experience building or experimenting with AI/GenAI solutions, LLMs, intelligent automation or machine learning is a strong plus.
Curiosity and willingness to learn new technologies quickly is critical for this role.
Business & Analytical Skills
Strong analytical and problem-solving skills with the ability to break down complex business problems into structured technical solutions.
Ability to understand business rules and translate them into data logic and scalable technical implementations.
Strong attention to detail, particularly given the financial and field-force impact of sales crediting and Incentive Compensation.
Ability to investigate ambiguous data issues, identify root causes and develop sustainable solutions.
Strong business acumen and ability to understand the "why" behind requirements rather than simply executing technical specifications.
Collaboration & Communication
Strong written and verbal communication skills with the ability to interact effectively with both technical and business stakeholders.
Ability to work independently while collaborating effectively across a matrix organization.
Strong ownership mindset with the ability to take accountability for platform performance and deliverables.
Comfortable working in a fast-paced environment with changing priorities.
Quick learner with high intellectual curiosity and a continuous improvement mindset.
Experience & Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Information Technology, Business Analytics, Statistics, Mathematics or a related discipline.
3–6 years of experience in data engineering, data analytics, business intelligence, data platforms or a similar technical role.
Strong hands-on experience with SQL and Python.
Experience working with Databricks or similar modern data platforms.
Experience building or managing data pipelines and working with large datasets.
Experience with cloud data platforms such as Azure, AWS or GCP is an advantage.
Experience with AI/GenAI, machine learning, automation or modern analytics technologies is strongly preferred.
Experience in pharmaceutical/biopharma commercial operations, Incentive Compensation, sales crediting, sales operations or field reporting is an advantage but not mandatory.
Experience with commercial datasets such as sales, prescription, customer, territory, alignment, CRM or field activity data is a plus.
Experience working with business stakeholders and translating business requirements into technical solutions.
We hire for skills and capabilities, not just credentials – if this role excites you, but doesn’t perfectly match your resume, we encourage you to apply anyway.
How We Work Where you work matters – because collaboration, innovation and patient impact happen in many settings. Our roles are structured across four work models: site-essential, site-by-design, field-based and remote-by-design. The model assigned to this role is based on its core responsibilities. Learn more at https://careers.bms.com/ways-of-working.
Supporting People with Disabilities 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 adastaffingsupport@bms.com. Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.
Candidate Rights BMS will consider qualified applicants with arrest and conviction records, pursuant to applicable laws in your area.
For roles based in Los Angeles County only: 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/
Data Protection We will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself at https://careers.bms.com/fraud-protection.
Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations. If this posting is missing required information required by local law or incorrect, contact BMS at TAEnablement@bms.com with the Job Title and Requisition number. Do not send application-related inquiries to this email. To check your application status, please login to your Candidate Home Account.
R1605919 : Data Analyst II, Incentive Compensation
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