Harvey Nash
Senior Clinical Data Manager

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Job Title: Senior Data Manager
Location: Welwyn Garden City, UK
Duration: 6 Months Contract
Mode of Work: Hybrid Role (2/3 Days in a Week)
The Opportunity:
The Data Manager (DM) plays a critical role in ensuring the quality, integrity, and availability of clinical trial data to support decision-making in early and late-stage drug development. Working closely with Biostatistics, Analytical Data Science, and cross-functional partners, the Data Manager leads the design, implementation, and oversight of data management activities across one or more studies. This includes database setup, data cleaning, query resolution, and vendor oversight, with a strong emphasis on regulatory compliance, efficiency, and data readiness for analysis.
The role requires both technical acumen and collaborative leadership to anticipate challenges, drive process improvements, and enable high-quality data delivery across the clinical portfolio.
- You independently manage end-to-end data management activities for one or more studies, from CRF and database design to final study closure
- You collaborate with cross-functional partners (Biostats, Data Science, Clinical) to define data specifications and ensure data meets study needs
- You collaborate with Clinical Operations to ensure optimal selection of data-related vendors and drive site performance in data entry timeliness and query resolution
- You resolve complex data issues using industry best practices, knowledge of risk-based monitoring, and system capabilities (e.g., EDC, ePRO, IRT)
- You evaluate and refine study-level data processes, incorporating feedback and innovations to improve efficiency and data quality
- You support oversight of third-party vendors to ensure data deliverables meet regulatory and quality expectations
- You share technical expertise with colleagues and contribute to continuous improvement of team practices and documentation
- You demonstrate a good understanding of the clinical data ecosystem, proactively identifying data issues, taking ownership of non-CRF data, and knowing where to go to resolve problems efficiently
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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Who you are:
- You hold a Bachelor’s (or Master’s) degree in computer science, life sciences, statistics, informatics, or a related field
- You have a minimum of 5 years of experience in clinical data management or a related function, or an advanced degree with 3 years of equivalent work experience
- You have hands-on experience managing data for clinical trials (e.g., CRF design, query resolution)
- You have working knowledge of EDC systems and data standards (e.g., CDISC)
- You have a solid understanding of clinical data types and how they relate to analysis
- You are able to work independently and prioritize across multiple deliverables
- You are familiar with risk-based monitoring or data quality metrics
- You demonstrate respect for cultural differences when interacting with colleagues in the global workplace


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Preferred:
- Programming literacy (e.g., SAS, R, Python) for data review or visualization
- Experience with early-phase data types or adaptive study designs
- Strong interpersonal and communication skills to coordinate with cross-functional partners
- Exposure to data flow across the clinical systems landscape (e.g., EDC to SDTM)
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