Senior Data Anonymization Analyst
Job ID: REQ-10060557
Location: Hyderabad, India
Employment Type: Full-time | Regular
About the Role:
We are seeking a Senior Data Anonymization Analyst to join our Data42 team at Novartis, contributing to global clinical research initiatives. The role focuses on anonymizing diverse datasets—including clinical trial raw and derived data, lab and third-party data, images, documents, and other unstructured data—to enable secondary research while mitigating the risk of re-identification of personal information.
This position requires close collaboration with cross-functional teams to ensure timely, accurate, and high-quality anonymization outputs. The ideal candidate will leverage programming expertise, statistical methodologies, and modern data platforms to drive innovative solutions in data anonymization.
Key Responsibilities:
Perform end-to-end data anonymization for clinical and non-clinical datasets in compliance with global standards.
Collaborate with internal and external Data Anonymization analysts on complex projects, making informed anonymization decisions and recommendations.
Communicate effectively with stakeholders, ensuring high-quality deliverables and timely reporting.
Maintain strong working relationships with cross-functional teams, providing updates on anonymization status and outputs.
Ensure adherence to industry standards (CDISC, SDTM/ADaM, eCTD, Define.xml) and company processes.
Conduct quality control, validation, and audit readiness for all anonymized datasets.
Innovate and implement efficiency improvements, including AI/LLM approaches for data anonymization.
Stay current on programming languages (SAS, Python) and platforms (Databricks, Palantir Foundry) to enhance data processing workflows.
Apply risk-based anonymization strategies and statistical methods to safeguard sensitive data.
Key Performance Indicators (KPIs):
Timely, high-quality anonymization deliverables.
Effective collaboration with cross-functional global teams.
Implementation of innovative solutions to improve anonymization efficiency.
Qualifications & Experience Required:
Education: BA/BS/MS in Statistics, Computer Science, Mathematics, Life Sciences (Genetics/Bioinformatics preferred), or equivalent international experience.
Experience: 4–5 years in pharmaceutical/clinical data programming or anonymization roles.
Proven experience with SAS programming and anonymization software.
Familiarity with risk-based anonymization methodology and CDISC standards.
Knowledge of Python and data platforms like Databricks or Palantir Foundry is advantageous.
Understanding of regulatory requirements relevant to statistical programming (GCP, study procedures).
Strong project management, teamwork, and communication skills, with experience working in global matrix organizations.
Attention to detail and a proactive approach to process improvement.
Languages: Fluent in English (written and spoken).
Why Join Novartis:
Novartis is dedicated to transforming the lives of patients and their families through innovative science. Joining our global team means collaborating with passionate professionals, fostering a culture of inclusion, and contributing to groundbreaking medical research.
Benefits:
Comprehensive professional development and learning programs
Competitive compensation and rewards
Inclusive and supportive work environment
Application & Accommodations:
Novartis is committed to accessibility and reasonable accommodations for individuals with disabilities. If you require assistance during the recruitment process, please contact: diversityandincl.india@novartis.com and reference Job ID REQ-10060557.
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