Director, Clinical Data Management

Stoke Therapeutics•Bedford, MA

1d•$225,000 - $244,000•Hybrid

About The Position

The Director of Clinical Data Management will be responsible for leading data management activities for one or more development programs and serves as the highest point of escalation within Data Management per assigned programs(s). This role will report to the VP Clinical Operations and be accountable for managing day-to-day operations of data management activities. The candidate will be responsible for oversight of Contract Research Organization (CRO) activities related to data management, including project management, vendor management, and coordination of internal reviews. Consistent with ICH E6(R3), the role champions a risk-based, quality-by-design approach to data management and data governance across the portfolio.

Requirements

Bachelor’s degree or higher in a scientific or healthcare discipline (advanced degree a plus), with 10+ years of progressive experience in data management within biotech, pharmaceutical, or CRO settings, including prior line-management / people leadership experience.
Rare Disease and Neurology trial experience are highly desirable.
Proficient in clinical data collection, cleaning and analysis for Phase I- IV clinical trials in the pharmaceutical industry.
Experience working in an outsourced data management model.
Knowledge of and experience with EDC databases CDISC standards (CDASH, SDTM and ADaM, including Define-XML), medical terminology, medical coding dictionaries (MedDRA, WHODrug), and quality control processes.
Working knowledge of GCP E6(R3), 21 CFR Part 11 and applicable FDA/EMA requirements, including risk-based quality management and data integrity (ALCOA+) principles.
Prior experience filing a BLA or NDA preferred.
Ability to manage multiple initiatives and shifting priorities within a small company environment.
Excellent interpersonal skills with the ability to work independently and collaboratively in a dynamic team environment.
Strong experience in early phase drug development and rare diseases required.
Microsoft Applications (Outlook, Word, Excel, PowerPoint, Project, Visio).
In depth knowledge of clinical data management systems (eg: Medidata Rave Veeva Vault CDMS) required; working familiarity with data review, visualization, and analytics tools (e.g., SAS, R/Python, Spotfire, Power BI, J-Review, or elluminate).

Nice To Haves

Advanced degree a plus
Rare Disease and Neurology trial experience are highly desirable.
Prior experience filing a BLA or NDA preferred.

Responsibilities

Accountable for data management activities for Stoke clinical studies and oversee CRO data management activities that support ongoing clinical programs.
Oversee data management activities for one or more product/programs, consisting of multiple clinical studies.
Manage a best in class Data Management team, consisting of highly qualified and experienced data managers.
Balance resources, and ensure appropriate levels to support organization activities (current and future).
Manage budgets and expenses, including budget projections.
Support inspection readiness, quality compliance, and training initiatives pertaining to Data Management activities.
Create SOP’s and standards for Data Management to support Stoke’s development programs.
Develop the Data Management Plan (DMP) across programs and maintain throughout lifecycle of study project to ensure DMP is followed according to study design and requirements.
Review clinical research documents (e.g. Protocols, Case Report Forms, Reports and Statistical analysis).
Review DB clinical trial data specifications, including eCRF design, user requirements, edit rules/checks, query logic and data validations.
Review Data Transfer Agreement(s) (DTAs) between external data vendors and/or core labs.
Reconcile electronic data transfers from vendor to Sponsor.
Oversee the User Acceptance Testing (UAT) by CRO and Coordinating UAT of eCRF build and validation documents, included but not limited to: edit check document, issue logs, UAT summary report.
Maintain/track EDC user management and other Clinical databases across allocated Clinical trials.
Ensure clinical data within EDC is of high quality to support lock/unlock and freeze/unfreeze as appropriate for statistical review, interim review, and or final database lock- included but not limited to: data reconciliation and/or coding.
Accountable for eCOA (eDiary/ePRO/ClinRO/ObsRO), wearable and sensor data, and other electronic data collection methods to make sure the design of data collection meets the scientific objective.
Assist in defining and/or creating data listings, summary table validation, data specifications and/or process data transfers in preparation for statistical review and/or data management audit.
Perform close-out audit, as specified, for closing of study trial in EDC or other clinical data management DBs.
Assist in reconciling AE/SAE data in Safety DB and/or other Data Management DB.
Coordinate and communicate with DB vendors on consistent basis to address. Clinical team’s requests, project plans, and/or eCRF development activities.
Participates in the preparation and presentation of data, when applicable.
Ensure data system compliance by following the established guidelines of national and international regulatory authorities. Helps to identify and troubleshoot operational problems, issues, obstacles, and barriers for studies and programs; Working with appropriate teams towards action and ensuring resolution.
Establish and oversee a risk-based quality management (RBQM) approach to clinical data, including the definition and ongoing monitoring of Key Risk Indicators (KRIs) and Quality Tolerance Limits (QTLs) in line with ICH E6(R3).
Drive data-driven oversight through centralized monitoring, data analytics, and review dashboards/metrics (e.g., Spotfire, Power BI, J-Review) to detect anomalies, outliers, and trends across studies.
Ensure data integrity and 21 CFR Part 11 compliance across EDC and external data sources, applying ALCOA+ principles and current computer system validation/assurance (CSV/CSA) expectations.
Promote standardization and automation (e.g., SAS, R, or Python) and evaluate emerging AI/ML-enabled tooling to improve the efficiency, consistency, and quality of data review and reporting.