Clinical Data Manager II

Collaborate with peers within function and across the organization to identify, design and execute fit for purpose data management solutions, ensuring FAIR principles are adhered to. Acts as experts for data collection and acquisition, advising teams and stakeholders on best practices and proposing innovative solutions such as the collection of new data types (e.g., emergent biomarkers), new technologies (e.g., sensors), and new data sources (e.g., EMR). Partner with and provide oversight of data management deliverables (e.g., Task Ownership Matrix) to our Functional Service Providers (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. Continue to be accountable for quality and provide business and technical expertise to our FSP as needed. 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 in data received, gaps in standard checks programmed or other unexpected anomalies in the data. As required, 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 and influence their understanding of decisions made in our function. Inform stakeholders of key deliverables and act on changing milestones. Vendor Management: 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. Data Collection and 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 applicable 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 in our data to ensure high quality results. Data Curation: Organization and integration of data collected from various sources. Maintain value of data through application of FAIR (Findable, Accessible, Interoperable, Reusable) principles. Support Analyses: Partner with stakeholders to understand their data insight needs and offer Data Management solutions. Demonstrate a strong understanding of the data flow from collection to analysis and filing (if applicable). Functional Excellence: Collaborate and contribute to functional/cross‑functional initiatives or goals to promote new ways of working, including emerging technologies. 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, CRO and collaborative groups on technical solutions to ensure high quality data collection and delivery. Deliver on solutions as needed. Minimum Qualifications BS or MS in Life Sciences, Data/Computer Science, Bioinformatics OR equivalent industry experience. Demonstrated strong collaboration and excellent communication skills – both written and oral (proficiency in English required). Knowledge of CDISC data standards. Knowledge of ICH‑GCP and working in 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. Demonstrated entrepreneurial mindset and self‑direction, ability to mentor others and willingness to learn new techniques. Knowledge of biological principles, display interest and demonstrate 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 start‑up, 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, as well as strong scientific and technical expertise. Extensive technical and or industry experience (for senior and principal roles). Experience in enterprise level operating systems and familiarity with databases. Fluency in programming languages (SAS, R, Python, SQL, etc). Some 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, Pharm D, PA or other applicable health professional qualification preferred. Job Competencies Strategic Agility / Teamwork and Collaboration – Understands and respects cultural differences when interacting with colleagues, whether locally or globally. Strategic Agility – Basic scientific understanding of the healthcare environment (e.g., regulatory, payers, medical practice) and regulatory guidelines in a pharmaceutical setting, as these relate to reporting requirements. 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 area(s) including throughout the lifecycle of a clinical study; study start up through database lock/close activities. 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 practice (example: GDPR). Staying informed with industry trends on new data collection technologies (example: new DM software/EDC systems, ePROs, etc) AND continued education/learnings to better understand other data sources (example: claims, EHRs, tele‑medicines and other novel platforms). Technical and Business Expertise: Innovation – Development and improvement of business and technical processes. Technical and Business Expertise: Teamwork and Collaboration – Project management skills (e.g., manage scope and effective delegation to other functions, staff, contractors and external vendors). Project management/oversight of all data management activities (data process & tools). Communication / Teamwork and Collaboration / Inspiring and Influencing – Communication and collaboration skills (including consulting skills, interpersonal skills to contribute effectively within- and across functional team settings, ability to influence others without authority, ability to build strong collaborative relationships with partners). Achieving Results – Drive for results (e.g., being proactive, demonstrates interest and ability to learn new things, takes initiative, welcomes problems as challenges; finds creative solutions in an ambiguous environment). Achieving Results – Degree of supervision to accomplish requirements. Feedback and Coaching – Ability and willingness to mentor other data managers. Pay ranges between 75‑80 /hr based on experience. #J-18808-Ljbffr