Study Data Manager I
1 DNA way South San Francisco, CA 94080
Bayside Solutions is seeking a Study Data Manager I to be part of our client’ s team in South San Francisco. This is an opportunity to work with the largest privately held pharmaceutical corporation in the world and ranks among the world' s 20 leading pharmaceutical corporations.
Our Client’ s culture is highly collaborative, offers an environment that encourages employees to expand their knowledge in order to make a profound impact on patients’ lives. This could explain why their company has been recognized as one of the “ Top Twenty Employers” in biotechnology and pharmaceuticals by Science Careers.
Our Company Bio: Bayside Solutions was founded in 2001, Bayside was recognized as one of the fastest growing professional staffing companies in Northern California. The numbers tell the story: We have close to a 100% client retention rate, 700% growth in four plus years and over 95% repeat business. Our dedication to building partnership relationships with both our clients and our recruits is the key to our phenomenal success.
You can find additional information on our company website at www.baysidesolutions.com.
Study Data Manager I
- An opportunity to join a patient-focused organization that is driven to develop, manufacture and commercialize medicines to treat life threatening conditions.
- Work for a company that is local to the bay area and recognized as a leader of innovation.
- Competitive compensation commensurate with experience.
- This position is eligible for medical, vision, dental benefits, paid sick time, and 401K.
Summary of Responsibilities:
- PROJECT MANAGEMENT: Develop risk management strategies and proactively manage timelines to ensure successful oversight and delivery of studies, projects and coding responsibilities, 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 status 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 a high quality of data and compliance with applicable pharma industry 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 through 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. 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.
Summary of Minimum Qualifications:
- BSc or MSc 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 environments.
- Project Management skills.
- Able to manage multiple requests and priorities.
- Demonstrated leadership capabilities around 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 an understanding of data types and their scientific use (clinical, biomarker, WGS, RNA-seq, etc.).
Summary of Preferred Qualifications:
- BSN, RN, RPh, Pharm D, PA or other applicable health professional qualification preferred or previous practical and theoretical experience of clinical coding
- Experience in leading CDM study teams and maintaining oversight of all start-up, conduct and close-out activities for multiple or complex studies, ensuring fit for purpose quality (including oversight of FSPs, Vendors, CROs and Collaborative Groups).
- Experience in leading the collection of clinical trial and/or Real World Data.
- Good understanding of molecule and disease area strategies, healthcare environments, as well as strong scientific and technical expertise.
- Extensive [technical] and/or [industry] experience required for senior/principal roles.
- Experience in enterprise level operating systems and familiarity with databases (Relational Database Management System, RDBMS).
- 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 or 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 (e.g., using Git, Rmarkdown) and literate programmer.
- Experience with SDTM implementation and CDISC standards.
- Experience with standardized terminologies such as MedDRA and WHODrug