Data Analyst II, Incentive Compensation

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. Roles & Responsibilities Sales Crediting Platform Ownership • 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. • 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, CR