Chief Risk Officer — Clinical Data Organisation

The mandate

A clinical-data organisation has developed an algorithm that identifies possible endpoint events from wearable, site and patient-reported data for expert adjudication. A sponsor plans to use the workflow in a pivotal study spanning conventional and decentralised sites. The algorithm does not make the final clinical determination, but it influences which records enter review and how quickly discrepancies are escalated.

The finding does not invalidate the underlying approach. It does expose a governance gap. Product, biostatistics, clinical quality, privacy and vendor teams each control part of the chain, while sponsor agreements describe the service as a whole. Existing assurance is strong at the system level but weaker around model change, population performance, device substitutions and the cumulative effect of manual fallbacks. The pivotal study cannot responsibly scale until risk acceptance and evidence are explicit.

The Chief Risk Officer will establish independent enterprise oversight across model, clinical, vendor, privacy, technology and continuity risk. Unlike the broader resilience role elsewhere in the market, this seat reports to the relevant board committee as well as the Chief Executive and will provide a separate view of whether the pivotal service is ready. The CRO will not take decisions away from medical, statistical, quality or sponsor authorities; they will ensure those decisions are based on reconciled evidence and fall within approved appetite.

The perimeter includes approximately 275 employees and material partners across Switzerland and international trial operations. The appointment is urgent and newly created, based on site in Zurich. It suits a leader who can make a proportionate stop-or-proceed recommendation under uncertainty and then maintain oversight without operating the service by committee.

Why this seat is open

The board created the CRO position after the simulation review. Risk responsibilities were previously distributed among quality, legal, information security and programme leadership. All remain important, but no independent executive was charged with aggregating the effect of model changes, device variation, vendor dependency and study commitments or with advising the board on residual exposure.

What you will own

• Establish the risk appetite and independent readiness criteria for algorithm-supported clinical-data services, including patient, evidence, regulatory, privacy and sponsor consequences.
• Review the event-identification workflow from source device and participant through ingestion, algorithm version, threshold, manual fallback, expert adjudication and reported endpoint.
• Create model-change governance covering intended use, version control, validation, subgroup performance, drift, exceptions, rollback and sponsor notification.
• Assess decentralised-trial vendors by workflow criticality, device and firmware control, data completeness, substitution practice, recovery and audit rights.
• Provide the board and sponsors with an integrated risk view while preserving the independent authority of quality, medical, privacy, security and statistical leaders.
• Lead a risk and assurance capability serving approximately 275 employees and partners, focusing resources on consequential pathways rather than uniform documentation.
• Review material client contracts and study changes for obligations that alter risk beyond approved assumptions or cannot be supported by available evidence.
• Govern incident thresholds and learning across studies, ensuring minor differences are analysed for cumulative bias rather than closed only as isolated operational exceptions.

The first 12 months

• Days 1–90: Reconstruct the threshold change and device-version findings, assess impact on simulated event capture and agree immediate controls. Establish independent pivotal-readiness criteria, clarify board escalation and require all material algorithm, device and fallback assumptions to be visible in one risk decision.
• Months 4–9: Complete prospective validation across representative devices, sites and relevant populations; test manual and outage fallbacks; and obtain sponsor agreement on change notification. Implement critical-vendor assurance and a model inventory tied to intended use, evidence owner and approved version.
• Months 10–12: Deliver an independent proceed, condition or pause recommendation before full pivotal expansion. Demonstrate effective monitoring of capture rates, missingness, drift and adjudication outcomes after launch. Complete the enterprise risk appetite and extend the method to other high-consequence data services without copying controls indiscriminately.

What the board will measure

• Pivotal readiness supported by prospective evidence across devices, sites and defined populations, with all conditions and residual risks explicitly owned.
• Complete traceability of algorithm versions, thresholds, inputs, fallbacks and adjudication for selected endpoint records.
• Detection and escalation of material performance differences before they distort study evidence, including subgroup and device-specific signals.
• Critical vendor compliance with device, change, recovery, audit and data-return requirements, verified through evidence and exercises.
• No client or study commitment that expands the service’s intended use or risk profile without approved validation and risk acceptance.
• Independent risk reporting that changes decisions where necessary while avoiding duplicate operational review and uncontrolled delay.

The person

You are a Chief Risk Officer, senior clinical quality or model-risk leader, or regulated-data executive with 22–28 years in clinical research, biotechnology, medical technology, health data or a comparable evidence-critical industry. You have provided independent oversight of an algorithm or complex data service used in a regulated decision. You have influenced at least 250 employees and controlled an assurance, risk or remediation perimeter of at least CHF 75 million.

You understand the limits of a “human in the loop” claim. You can test whether an algorithm affects selection, prioritisation or omission before expert review, and therefore what validation and monitoring are required. You have governed model or rules changes, assessed population and device effects, and can explain the resulting risk to clinicians, statisticians, engineers and directors.

Relevant adjacent backgrounds include medical devices, pharmacovigilance, regulated analytics, financial model risk or safety-critical technology, provided the candidate can demonstrate rapid command of clinical evidence and patient-data obligations. A policy-only risk career will not fit. Direct experience with decentralised studies, wearable data or endpoint adjudication is strongly preferred.

The CRO will be based in Zurich and travel selectively for sponsor, vendor and site assurance. The board seeks independence without detachment: a leader willing to pause expansion when evidence is insufficient, and equally willing to approve a bounded route when controls and monitoring make the residual risk acceptable.

Compensation and terms

The indicative base salary is CHF 340,000–470,000, accompanied by annual incentive and long-term participation. Measures will reflect independent decision quality, pivotal readiness, early risk detection, vendor control and practical adoption of the framework. The permanent appointment carries dual accountability to the Chief Executive and relevant board committee. Relocation and verified forfeited awards may be considered.

Confidentiality

The client, sponsor, study, algorithm and device providers are confidential. Identifying evidence will be released only after candidate relevance is established and the required agreement is signed. Applicants must not search trial registries or contact vendors in an attempt to identify the organisation.

Each response must contain no more than 49 words.