Clinical Data Manager II

Job Summary Job Title: Clinical Data Manager II Work Location: San Francisco, CA (Hybrid) Interview Model: 1. Phone screening (15-20 minutes). 2. Virtual panel interview Contract: W2 Description Summary of Opportunity Oversee collection and validation of clinical data. Develop and manage clinical databases. Ensure data quality and compliance with regulatory requirements. Collaborate with cross‑functional teams for data reporting. Support audits and inspections related to clinical data. Who You Are 5–10 years of experience. Strong problem‑solving skills. Excellent communication abilities. Knowledge of GCP and clinical regulations. Job Description Data Manager/Data Quality Leader reporting function: US Medical Affairs Evidence Generation/Data Systems. Reports to the DM Manager. Direct reports: None. Position Summary: The DATA MANAGER works within a team of experts in data life‑cycle management who acquire and curate data for use in exploratory research, clinical development and evidence generation. The role collaborates with peers within the function and across the organization to identify, design, and execute fit‑for‑purpose data management solutions, adhering to FAIR principles. Responsibilities include ensuring timely completion of data management deliverables and partnering with Functional Service Providers (FSPs), DM CROs and other vendors, overseeing and providing technical expertise in the delivery of high quality data. The manager also contributes to functional, cross‑functional, enterprise‑wide or external initiatives that shape our technical landscape, business and healthcare environments. Strong strategic, collaboration and communication skills and an entrepreneurial mindset are required. Role: Data Quality Leader Tasks Collaborate with peers within the function and across the organization to identify, design, and execute fit‑for‑purpose data management solutions, ensuring FAIR principles are adhered to. Act as experts for data collection and acquisition, advising teams and stakeholders on best practices and proposing innovative solutions, including new data types, technologies, and sources. Partner with and provide oversight of data management deliverables to FSPs and vendors. Provide quality assurance on tasks as applicable to ensure a high quality of data and compliance with applicable pharma industry regulations and standards. Proactively manage timelines and track decisions, ensuring successful delivery of the study SOW carried out by FSP. Oversee sample management and eManifest process, ensuring timely, proactive resolution of queries. Provide high‑level review of data using graphical visualizations, statistical monitoring tools, and standard metrics designed to identify outliers or trends. Be the BDS DM representative on the SMTs and any associated meetings such as Data Quality meetings. Proactively engage with stakeholders across the business and biometrics to understand their needs and influence their understanding of decisions made on our function. Partner with relevant functions for external data vendor selection and management. Oversee development of data transfer agreements with vendors ensuring use of standards, fit‑for‑purpose data models and transfer intervals. Contribute to functional, cross‑functional, enterprise‑wide or external initiatives that shape our future landscape. Major Responsibilities Project Management – Develop risk management strategies and proactively manage timelines to ensure successful oversight and delivery of studies & projects, including the implementation and adoption of new technologies. Stakeholder Management – Proactively engage with stakeholders across the business to understand their needs, inform them of key deliverables and act on changing milestones. Vendor Management – Partner with relevant functions for external data vendor selection and management, and oversee development of data transfer agreements with vendors. Data Collection & Acquisition – Act as experts for data collection, advising teams and stakeholders on best practices and proposing innovative solutions. Ensure high quality data and compliance with regulations and standards. Provide Data Solutions – Stay current with and adopt emergent data collection, data management, visualization and provision tools and applications to ensure fit‑for‑purpose and impactful approaches. Deliver on solutions as needed. Data Quality Review – Use data surveillance tools and strategies to provide aggregate level reviews designed to identify patterns or anomalies to ensure high quality results. Data Curation – Organization and integration of data collected from various sources. Maintain value of data through application of FAIR principles. Support Analyses – Partner with stakeholders to understand their data insight needs and offer Data Management solutions, demonstrating a strong understanding of the data flow from collection to analysis and filing. Functional Excellence – Collaborate and contribute to functional/cross‑functional initiatives or goals to promote new ways of working, including emerging technologies, and enable broader and more effective use of data to support the business. Technical Consultant – Offer guidance and advice to peers within the function, to key stakeholders, and to FSPs, CROs, and collaborative groups on technical solutions to ensure high quality data collection and delivery. Minimum Qualifications BS or MS in Life Sciences, Data/Computer Science, Bioinformatics, or equivalent industry experience. 5–10 years of experience. Strong collaboration and excellent communication skills (both written and oral, proficiency in English required). Knowledge of CDISC data standards. Knowledge of ICH‑GCP and experience working in a regulated environment. Project Management skills – Able to manage multiple requests and priorities. Demonstrated leadership capabilities and decision‑making, negotiation, motivation (self and others), and influencing. Experience with data analytics and/or visualization tools and techniques. Entrepreneurial mindset and self‑direction, ability to mentor others and willingness to learn new techniques. Knowledge of biological principles and scientific curiosity, including understanding of data types and their scientific use (clinical, biomarker, WGS, RNA‑seq, etc). Preferred/Additional Qualifications Experience in leading DM study teams and maintaining oversight of all startup, conduct and close‑out activities for multiple complex studies, ensuring fit‑for‑purpose quality. Experience in leading the collection of clinical trial and/or Real World Data. Good understanding of molecule and disease area strategies, healthcare environment, and strong scientific and technical expertise. Extensive technical and or industry experience. Experience in enterprise‑level operating systems and familiarity with databases. Fluency in programming languages (SAS, R, Python, SQL, etc.). Experience with advanced analytics approaches (e.g., machine learning, AI). Experience with tools related to technologies required to undertake analyses on large data sources with computationally intensive steps (SQL, parallelization, Hadoop, Spark, etc.). Experience producing interactive outputs (e.g., Shiny, Tableau). Contributor to open source packages, libraries or functions. Experience implementing reproducible research practices like version control and literate programmer. Experience with SDTM implementation and CDISC standards. Experience with standardized technologies such as MedDRA and WHODrug. BSN, RN, RPh, PharmD, PA or other applicable health professional qualification preferred. Job Competencies Strategic Agility / Teamwork and Collaboration – Understands and respects cultural differences when interacting with colleagues locally or globally. Strategic Agility – Basic scientific understanding of the healthcare environment, regulatory, payers, medical practice. Technical and Business Expertise: Management of Data for clinical studies – Knowledge and experience in data management as applied to clinical projects in specific/all therapeutic areas, including throughout the lifecycle of a clinical study. Technical and Business Expertise: Data Management Industry Standards – Knowledge and experience with CDISC/CDASH; application of data standards or common data model in clinical studies; compliant with HIPAA and other current patient privacy practices (GDPR). Technical and Business Expertise / Innovation – Development and improvement of business and technical processes. Technical and Business Expertise / Teamwork and Collaboration – Project management skills and oversight of all data management activities. Communication / Teamwork and Collaboration / Inspiring and Influencing – Communication and collaboration skills, consulting skills, interpersonal skills. Achieving Results – Drive for results: proactive, learns new things, takes initiative, finds creative solutions in ambiguous environment. Achieving Results Degree of supervision to accomplish requirements. Feedback and Coaching – Ability and willingness to mentor other data managers. #J-18808-Ljbffr IT Engagements