Bristol Myers Squibb had H-1B petitions approved for 240 workers in fiscal year 2025 (USCIS). That is history, not a promise for this role. See the record
At a glance
Data Analyst II, Incentive Compensation at Bristol Myers Squibb, an on-site role based in Hyderabad, India. Experience level: 6 Years. Posted on 10 November 2026, read from Bristol Myers Squibb's own careers page (Workday), which RealAnalystJobs re-checks daily and removes the role when it closes.
Similar roles on RealAnalystJobs, as of 10 November 2026
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.
Position: Data Analyst II, Incentive Compensation
Location : Hyderabad, India
At Bristol Myers Squibb, we are inspired by a single vision – transforming patients’ lives through science. In oncology, hematology, immunology and cardiovascular disease – and one of the most diverse and promising pipelines in the industry – each of our passionate colleagues contribute to innovations that drive meaningful change. We bring a human touch to every treatment we pioneer. Join us and make a difference.
Position Summary.
The Data Analyst / Data Engineer will be responsible for managing and continuously enhancing an in-house Sales Crediting Platform within the Incentive Compensation organization. The platform is a critical component of the Incentive Compensation ecosystem and enables accurate, scalable and timely sales crediting for the commercial field force. The role will combine data engineering, analytics, platform operations and business problem-solving, requiring the ability to translate complex business rules and data requirements into robust technical solutions. The individual will work closely with Incentive Compensation, Commercial, Data & Analytics and IT stakeholders to manage data pipelines, implement and validate sales crediting rules, troubleshoot data and processing issues, automate operational processes, and continuously improve the platform.We are looking for a technology-oriented, highly curious and hands-on individual who is comfortable working with large and complex datasets and is excited about applying modern technologies such as Python, Databricks, AI/GenAI and automation to transform Incentive Compensation processes.
Key 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
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