Senior Analyst

About the job

-Provide analytics support to Novartis internal customers (CPOs & Regional marketing and sales teams) on various low-medium complexity analytical reports. -Support and facilitate data enabled decision making for Novartis internal customers by providing and communicating qualitative and quantitative analytics. -Support GBS -GCO business in building practice by involving in various initiatives like knowledge sharing, onboarding and training support, support team lead in all business related tasks / activities, building process documentation and knowledge repositories. -To be an integral part of a comprehensive design team responsible for designing promotional marketing materials. Job Description Key Responsibilities • Collaborate with stakeholders and systems teams to create data products and business use cases that enable informed decision-making for business teams. • Curate data by applying standard quality and security checks to ensure accuracy and compliance. • Drive data enablement initiatives to align with the organization’s Data Strategy and DLC products/assets. • Ensure adherence to regulatory requirements and continuously improve quality-related processes within the scope of responsibility. • Deliver on data strategy priorities and DLC activities in an agile manner, maintaining proper documentation and clear communication throughout service delivery. Essential Requirements • 3-5 years’ experience in a Global company as a data steward, engineer, modeler or data scientist. • Business understanding of pharmaceutical industry and data standards. Domain experience in at least one of the following areas – a) Pharma R&D, b) Manufacturing, Procurement and Supply Chain and c) Marketing and Sales. Experience in working in Pharma / Life Science industry strongly preferred. • Hand on experience in working with ETL process, DWH Concepts, and programming/scripting skills (Python) for data preparation and analysis. • Excellent SQL Knowledge and zeal to learn new technology stacks. • Understanding of data modeling (conceptual, logical, and physical) using different data modeling methodologies. • Experience in data wrangling including Ingestion, Unification, Anonymization, Search, Master & Meta Data Management and Governance. • Excellent communication and presentation skills with consulting and senior stakeholder engagement experience. • Foundational understanding of semantic web principles, big data ecosystem, knowledge of AWS, AZURE Stack and basics of Gen AI, NLP would be an advantage. Desired Requirements • Exposure to data strategy implementation within large organizations. • Strong analytical and problem-solving skills with a focus on continuous improvement.

Requirements

• Amazon Web Services (AWS)
• Collaborating
• dataiku
• Dataiku Data Science Studio (DSS)
• Data Ingestion
• Data Processing
• Data Quality
• Data Warehouse
• Data Warehouse Management
• Data Warehousing (DW)
• etl
• excel
• Extract Transform Load (ETL)
• healthcare
• Health Care
• Microsoft Excel
• Pharmaceutical Industry
• Problem Solving
• Python (Programming Language)
• snowflake
• Snowflake (Platform)
• Snowflake Data Warehouse
• Structured Query Language (SQL)
• Supply Chain

Preferred Technologies

• Amazon Web Services (AWS)
• Collaborating
• dataiku
• Dataiku Data Science Studio (DSS)
• Data Ingestion
• Data Processing
• Data Quality
• Data Warehouse
• Data Warehouse Management
• Data Warehousing (DW)
• etl
• excel
• Extract Transform Load (ETL)
• healthcare
• Health Care
• Microsoft Excel
• Pharmaceutical Industry
• Problem Solving
• Python (Programming Language)
• snowflake
• Snowflake (Platform)
• Snowflake Data Warehouse
• Structured Query Language (SQL)
• Supply Chain