Clinical Data Manager

Clinical Data Manager

Location:

Pune, India – On-site (Balewadi)

Company:

Dizzaroo Pvt Ltd

Experience:

2–5 years

Employment Type:

Full-time

About Dizzaroo

Dizzaroo is an AI-first life sciences technology company building intelligent platforms for clinical research, translational biology, digital pathology, and pharmaceutical knowledge management. We are developing tools that combine clinical domain expertise, data science, and artificial intelligence to improve how clinical studies are designed, executed, reviewed, and interpreted.

We are looking for an early-career Clinical Data Manager who is motivated, detail-oriented, and interested in working at the intersection of clinical research, data management, and AI-enabled workflows.

Role Summary

The Clinical Data Manager will support the setup, maintenance, and oversight of clinical study databases and data management processes. This role is ideal for someone with 2–5 years of experience in clinical data management who understands EDC systems, clinical trial data flow, data cleaning, query management, and documentation.

In addition to traditional clinical data management responsibilities, this person should be open to learning and using AI tools to improve productivity, automate repetitive tasks, support data review, assist in SOP development, and contribute to the creation of next-generation clinical data platforms.

Key Responsibilities

Clinical Database and EDC Management

• Support the build, testing, and maintenance of clinical study databases in EDC platforms.
• Assist in eCRF design, edit check specifications, user acceptance testing, and database validation activities.
• Support study start-up, database updates, mid-study changes, and database lock activities.
• Work with clinical, medical, statistics, programming, and technology teams to ensure study data is collected accurately and efficiently.
• Maintain study-specific data management documentation, including data management plans, completion guidelines, query guidelines, and database specifications.

Data Review and Cleaning

• Perform routine clinical data review and data cleaning activities.
• Generate, review, and manage data queries.
• Identify data inconsistencies, missing data, protocol deviations, and potential data quality issues.
• Support reconciliation activities, including external/vendor data, safety data, laboratory data, imaging data, and other clinical data sources.
• Help prepare data listings, dashboards, and review outputs for clinical and medical review teams.

SOPs, Process Development, and Quality

• Assist in developing and maintaining SOPs, work instructions, templates, and checklists for clinical data management.
• Support the creation of scalable and inspection-ready data management processes.
• Contribute to quality control of data management deliverables.
• Help establish documentation practices aligned with GCP, regulatory expectations, and clinical trial quality standards.

AI-Enabled Clinical Data Workflows

• Use AI tools responsibly to support data review, documentation, process improvement, and workflow automation.
• Help test and improve AI-assisted clinical data review tools.
• Translate real clinical data management workflows into requirements for software and AI engineering teams.
• Identify repetitive data management tasks that can be automated or improved using technology.
• Participate in building modern, AI-enabled clinical data management systems.

Required Qualifications

• Bachelor’s or Master’s degree in life sciences, pharmacy, clinical research, biotechnology, statistics, computer science, or a related field.
• 2–5 years of experience in clinical data management, clinical research, or related clinical trial operations.
• Hands-on experience with at least one EDC platform.
• Understanding of clinical trial data flow, eCRFs, edit checks, query management, data cleaning, and database lock processes.
• Familiarity with GCP, clinical trial documentation, and data quality expectations.
• Strong attention to detail and ability to work with structured clinical data.
• Good written and verbal communication skills.
• Ability to work independently while collaborating with cross-functional teams.

Preferred Qualifications

• Experience with oncology clinical trials.
• Familiarity with CDISC standards, including SDTM concepts.
• Experience with Medidata Rave, Veeva, Oracle Clinical, REDCap, Castor, OpenClinica, or similar systems.
• Exposure to clinical data listings, medical review listings, discrepancy management, or data review dashboards.
• Basic understanding of SQL, Excel, Python, or data visualization tools.
• Experience preparing data management plans, edit check specifications, CRF completion guidelines, or SOPs.
• Interest in AI, automation, clinical technology platforms, and modern clinical trial data workflows.

Ideal Candidate Profile

We are looking for someone who is:

• Smart, curious, and willing to learn quickly.
• Comfortable working in a startup environment.
• Strong in clinical data management fundamentals.
• Interested in using AI tools to improve how clinical research work is done.
• Detail-oriented but also able to think about process improvement.
• Comfortable working with both clinical experts and software/AI engineers.
• Motivated to grow into a broader clinical data leadership role over time.

What You Will Work On

You may contribute to projects such as:

• Building and maintaining clinical study databases.
• Supporting data review workflows for clinical trials.
• Creating SOPs and clinical data management process documents.
• Testing AI-assisted data review tools.
• Helping define requirements for clinical data platforms.
• Supporting the development of tools that convert clinical questions into structured data review outputs.
• Improving how clinical trial teams identify discrepancies, missing data, and quality issues.

Why Join Dizzaroo

• Work at the intersection of clinical research, AI, and software product development.
• Contribute to tools that may reshape how clinical data management and clinical review are performed.
• Gain exposure to both traditional clinical data management and next-generation AI-enabled workflows.
• Work closely with a multidisciplinary team across clinical research, software engineering, AI, and life sciences.
• Opportunity to grow with an early-stage company building platforms for the future of drug development.