Clinical Data Manager

Planet Pharma; Arizona; On-site; USD 85,000 - 120,000; Full time

Job summary

Planet Pharma seeks a Clinical Data Manager to oversee data collection, cleaning, validation, and EDC system activities across assigned trials. The role emphasizes Python scripting for automation, data transformations, and ensuring GCP/21 CFR Part 11 compliance while collaborating with cross-functional teams including operations and biostatistics.

Qualifications include a Bachelor’s degree in Life Sciences or related field, 2+ years in clinical data management, and experience with Medidata Rave

Qualifications

• 2+ years of clinical data management experience within clinical trials.
• Advanced Python scripting for automation and data manipulation.
• Experience with EDC platforms like Medidata Rave, Veeva Vault CDMS, REDCap, Oracle InForm.
• Proficiency in GCP, 21 CFR Part 11, and regulatory audit readiness.

Responsibilities

• Oversee data collection, cleaning, and validation across assigned trials.
• Design, develop, and test EDC systems, UAT, and data validation specs.
• Manage query generation, reconciliation, and resolution with sites and CRO partners.
• Develop and execute Python scripts to automate data extraction, validation, and metrics reporting.
• Collaborate with Clinical Operations, Biostatistics, QA, and Site Management to meet milestones.

Skills

Python scripting

SQL

R

SAS

Education

Bachelor's Degree in Life Sciences, Computer Science, Health Informatics, Data Science, or related field

Master's degree preferred

Tools

Medidata Rave

Veeva Vault CDMS

REDCap

Oracle InForm

Job description

Primary Responsibilities

Data Management & Database Development

Oversee data collection, cleaning, and validation activities across assigned clinical trials to ensure high data quality, accuracy, and completeness.

Participate in the design, development, and testing of Electronic Data Capture (EDC) systems, user acceptance testing (UAT), and data validation specifications.

Manage query generation, reconciliation, and resolution workflows, working closely with clinical trial sites and CRO partners.

Technical Scripting & Workflow Automation

Develop and execute custom Python scripts and software utilities to automate data extraction, validation, routine cleaning checks, and metrics reporting.

Evaluate trial data infrastructure to identify technical bottlenecks, implementing software solutions that enhance processing speed and data accuracy.

Partner with technical and biostatistics teams to streamline data transformations and standardizations (e.g., CDISC SDTM/CDASH).

Compliance, Audits & Cross-Functional Collaboration

Ensure all clinical data management activities strictly adhere to Good Clinical Practice (GCP), ICH guidelines, FDA regulations, and standard operating procedures (SOPs).

Prepare, maintain, and review clinical data management documentation for regulatory inspections and quality audits.

Collaborate cross-functionally with Clinical Operations, Biostatistics, Quality Assurance, and Site Management teams to achieve trial milestones on schedule.

Qualifications & Key Requirements

Experience & Education

Education: Bachelor's Degree in Life Sciences, Computer Science, Health Informatics, Data Science, or a related field. Master's degree is a plus.

Professional Experience: Minimum of 2+ years of clinical data management experience within clinical trials (0-5 years total professional experience).

Technical Scripting: Advanced hands-on proficiency in Python for script automation, data manipulation, and software integration. Familiarity with additional programming languages (e.g., SQL, R, or SAS) is strongly desired.

EDC Systems: Practical experience working with industry-leading EDC platforms (e.g., Medidata Rave, Veeva Vault CDMS, RedCap, or Oracle InForm).

Regulatory Knowledge: Solid understanding of GCP standards, 21 CFR Part 11, and regulatory audit readiness expectations.

Soft Skills & Core Attributes

Initiative & Drive: Self-motivated mindset with a strong track record of taking ownership of projects and driving results independently.

Problem-Solving: Strong analytical capabilities with meticulous attention to detail in high-volume, complex data environments.

Collaboration & Communication: Excellent written and verbal communication skills; ability to articulate technical data solutions clearly to non-technical stakeholders.