Data Analyst II, Incentive Compensation

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 .

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.

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.

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.

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.

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.

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.

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