Clinical Data Management is evolving towards data lifecycle management for clinical development, as well as new data sources and the needs of advanced analytics. Where our work was once tool-centric we now look to be people and data centric. Processes that once focused on tools or systems are shifting focus to accommodate new data sources and types and will enhance productive dialogue and connection between all people delivering the work.
The new job description at Roche for a Data manager covers two roles; data quality lead and data engineer which offers individuals great opportunity to learn/support.
We currently have two open opportunities within our Clinical Data Management function, one is geared towards the technical data management aspects and the other being a project manager within data management of a study. But not limited to.
As a data manager within our Clinical Data Management (CDM) function you will work 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. You will collaborate with peers within the function and across the organization to identify, design and execute fit for purpose data management solutions, adhering to F.A.I.R. (Findable, Accessible, Interoperable, Reusable) principles. You will ensure the timely completion of data management deliverables and partner with Functional Service Providers (FSPs) and vendors, overseeing and providing technical expertise in the delivery of high quality data. You may also contribute to functional, cross functional, enterprise-wide or external initiatives that shape our technical landscape, business and healthcare environments. You will need strong strategic, collaboration and communication skills, as well as an entrepreneurial mindset, to evolve the way we collect and deliver data and to develop and deliver medicines for our patients.
As Data Manager you will be accountable for study/studies and non-study project deliverables. You partner with cross-functional teams and external partners and work with considerable independence.
- Lay the groundwork for our data users to analyze and visualize our clinical data. Manage data sources and databases and launch tools to enable decision making and drive new scientific insights. Develop, maintain, evolve and own systems, tools, scripts and processes that enable the delivery of FAIR data.
- Continue to provide technical expertise (Rave, Spotfire, SDTM) to our study teams, both at the FSP and internal teams. Resourced as a technical SME on our work packages for very complex or specialized study builds.
- Provide technical expertise to technical projects and initiatives, adding programming expertise in the delivery of these projects. E.g., Data Surveillance, Data Flow.
- Provide reports, listings and visualizations to stakeholders, using Spotfire, Tableau or ‘R’ on an ad-hoc basis and when required, using scientific and technical know-how to understand the user requests to propose and provide the appropriate solution to present this data.
- 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.
- Contribute to the programming of and ongoing maintenance of Centralised Monitoring and Data Surveillance tools.
- Act as experts for data collection and acquisition, advising teams and stakeholders on best practices and proposing innovative solutions. e.g. the collection of new data types (e.g. emergent biomarkers), new technologies (e.g. sensors), and new data sources (e.g. RWD, EMR).
- Partner with and provide oversight of data management deliverables (e.g. Work-Packages) 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 work packages carried out at FSPs. Continue to be accountable for quality and where needed, provide support in the form of business and technical expertise to our FSPs.
- Oversee FSP in Sample management and eManifest process, ensuring timely, proactive resolution of queries.
- 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.
- 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.
- 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.
- 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.
- 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.
- BSc or MSc in Life Sciences, Data/Computer Science, Bioinformatics OR equivalent industry experience.
- 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.
- 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.).
- Extensive [technical] and/or [industry] experience required for senior roles.