Senior Analyst at Novartis

Hyderabad, Telangana, India -

Full Time

Start Date

Immediate

Expiry Date

24 Apr, 26

Salary

0.0

Posted On

24 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Steward, Data Engineer, Data Modeler, Data Scientist, Pharmaceutical Industry, ETL Process, DWH Concepts, Python, SQL, Data Modeling, Data Wrangling, Data Quality, AWS, Azure, Gen AI, NLP

Industry

Pharmaceutical Manufacturing

Description

Job Description Summary Your responsibilities include, but not limited to: Help in creation of data products/business use cases to by working with relevant stakeholder, systems to solve and enable business team’s decision making. Ensure data curation by applying appropriate standard Quality & Security checks Ensures the data Enablement to ensure they are fully aligned and support the Data Strategy and the DLC products / assets Ensure compliance with GMP and regulatory requirements and continuous improvement of quality relevant processes within area of responsibility Deliver on data strategy priorities and DLC activities in an AGILE manner with appropriate documentation and communication throughout the delivery of services 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 Skills Desired Amazon Web Services (AWS), Data ETL, dataiku, Dataiku Data Science Studio (DSS), Data Quality, python, Python (Programming Language), snowflake, sql, Structured Query Language (SQL) Improving the lives of people living with disease takes more than innovative science. It takes a focus on the needs of people and a community committed to meeting them. It takes a team of people like you. Working together. Learning together. Thriving together. Discover how you can join us in changing people’s lives. In the context of China Cross-Border Data Transfer (CBDT) policy, if you need to apply for a position in China, please go to the local Recruiting System TaleNov .

Responsibilities

The Senior Analyst will collaborate with stakeholders to create data products and business use cases that support decision-making. They will also ensure data quality and compliance with regulatory requirements while delivering on data strategy priorities in an agile manner.