Data Warehousing


Strategic and execution-driven data leader with over 16 years of experience in driving AI/ML-enabled commercial transformation within the pharmaceutical and life sciences sectors. Expertise in building and scaling robust machine learning products across 25+ global markets, enhancing customer experience analytics, and facilitating omnichannel engagement at scale. Currently spearheading AI/ML product initiatives that integrate data governance through Unity Catalog, model lifecycle management, and foster cross-functional collaboration among commercial, medical, and data science teams. Committed to leveraging data-driven insights to propel organizational growth and innovation.
As Product Owner and Delivery Lead, I drive the design, build, and deployment of ICE models by aligning business priorities with technical capabilities. The Intelligent Cognitive Engine's next-generation AI framework, nAvIn, integrates model construction, activation, and operations under a single operating model that is led by a single product. By standardizing key machine learning procedures, it streamlines demand-to-value delivery while enabling BU and DD&T to adapt models for local impact.
As a Solution Architect (Data), I am defining the global data management strategy for GPD, establishing data governance, creating the enterprise data model for commercial applications, establishing policies and guidelines for all commercial data, designing the database for all transactional and data warehouse systems, defining the canonical messages for SOA-based system integration, and developing a Data Quality Framework.
As a Solution Architect (Data), I am defining the global data management strategy for GEM, establishing data governance, creating the enterprise data model for commercial applications, establishing policies and guidelines for all commercial data, designing the database for all transactional and data warehouse systems, and defining the system integration.
As Solution Architect in designing the flow and overall implementation of engineering efforts. Partner with clients to capture requirements and develop solutions. Earlier been part of multiple development, enhancements, customizations and Operations. Guide a team of 20 resources in providing business and technical support of Commercial Operations Analytical Dashboards and Data Warehouse. Ensure the successful communications between multiple cross-functional and client-facing departments, including business liaisons, vendors and program management resources. Visit with business to understand their needs and address their requirements and necessities; proposed solutions to complex challenges risks and presented mitigation strategies to improve client relations.
Designed and developed the 'People Make the Difference Real Performance Management' tool to calculate specific metrics for each site, retailer, and field user; qualified bonuses for top performers ranked within each category. Provided technical leadership to six resources while guiding them through the full project lifecycle. Collaborated with functional leaders, and provided consulting services for open markets.
Directed all aspects of knowledge transfer with both internal and external teams. Performed GAP analysis to identify opportunities for improvement, and operated as a business analyst to capture requirements and critical scope.
Positioned to provide a tactical review of the architecture and business framework. Served as the subject-matter expert for the recalibration of internal business intelligence and standardized reports for daily, weekly, monthly, and quarterly updates.
Partnered with business leaders to establish a pragmatic data migration scope, planning, and execution protocol. Operated as the Lead Developer for BI initiatives, data warehousing, and report creation.
Established applications, data files, and client-facing documentation according to internal best practices. Recognized the immediate need to enhance testing code, quality control efforts, and business requirement requests.
Management of AI and ML products
Data-driven omnichannel insights
Lifecycle governance in MLOps
Data architecture design
Stakeholder collaboration
Experience with agile frameworks
Data-driven business analysis
Agile project management
Design thinking
Data-informed decision making
Advanced technical skills
Data Warehousing
Data Governance
Data Visualization
Machine Learning
Omni Channel
Salesforce Effectiveness
Artificial Intelligence