Clinical Data Analytics Lead

Novartis

Hyderabad (Office) +1 more Onsite Research & Development

About this role

Job Description Summary

Drive cross-functional strategy for clinical data analytics and solutions that advance risk-based insights, boost operational efficiency by focusing on critical to quality, and ensure high-quality data outcomes for Clinical Data Operations (CDO) for the assigned portfolio.

Lead the end-to-end design, and implementation of innovative clinical data analytics & reporting solutions, partnering closely with key stakeholders to enable data-driven decision-making and continuous improvement across the organization.

Job Description

Key Responsibilities

Support DM Leads and Data Quality Teams (DQT) in deriving and articulating both planned and ad-hoc clinical and operational data insights.
Drive cross-functional collaboration to enhance data strategy, quality, site experience, and patient safety using disease area, protocol, and data standards expertise.
Partner with Central Monitoring (CM) and Risk-based Quality Management (RbQM) leads to promote risk-based data review approaches.
Act as a data review solution advisor, translating complex insights into clear, actionable recommendations for stakeholders.
Contribute to exploratory data quality management plans in collaboration with DQT.
Enable detection of data discrepancies and anomalies by supporting deployment of user-friendly analytical tools.
Promote responsible AI adoption, develop proof-of-concepts (PoCs), and support product ionization of approved use cases.
Identify opportunities to optimize analytics processes and improve solution performance.
Stay current with emerging technologies, trends, and best practices in data analytics, automation, and AI.
Develop and maintain technical documentation while fostering a culture of innovation and continuous learning.

Minimum Requirements

Strong experience in clinical data management with expertise in RbQM, analytics, and driving operational excellence in pharma/clinical research.
Proficiency in clinical data technologies (EDC, data hubs, metadata tools), standards (CDISC SDTM/ADaM), and regulatory/data governance frameworks.
Exposure to AI/ML, automation, cloud, BI tools (Power BI, Tableau), and programming (SAS, R, Python) with strong ability to translate complex insights into clear stakeholder communication.

Skills Desired

Classification Systems, Clinical Trials, Computer Data Storage, Computer Programming, Cross-Functional Teams, Data Analysis, Data Structures, Initiative, Programming Languages, Reporting, Statistical Analysis