Chief Data Officer — Precision-Oncology Portfolio

The mandate

A precision-oncology company has assembled clinico-genomic data through agreements with several hospital systems and specialist laboratories. The dataset has supported target selection and protocol design. Management now proposes to use a defined cohort as external evidence alongside a pivotal study in a rare molecular population. The approach could reduce enrolment burden and improve context for outcomes, but only if treatment history, testing practice, endpoint ascertainment and follow-up can be made comparable enough for the intended question.

An initial feasibility analysis produced an attractive survival curve. A deeper review found material differences among institutions: sequencing panels changed over time, lines of therapy were derived using different rules, and patients lost to follow-up were not random. Consent and contractual terms also differ for research, regulatory submission and future model development. None of this makes the data unusable. It does mean that the current “one dataset” description conceals choices that must be governed before pivotal commitments are made.

The Chief Data Officer will own the enterprise data strategy and the fitness of evidence derived across clinical, molecular and research sources. The role covers provenance, common definitions, data partnerships, privacy and consent interfaces, data product stewardship, analytics engineering and decision-grade evidence. Biostatistics and medical leaders remain accountable for analysis and clinical interpretation; the CDO ensures that the data entering those decisions is understood, traceable and used within permission.

The broader perimeter includes approximately 280 employees and material partners, with the principal base in San Diego. This is a planned new appointment reporting to the Chief Executive or designated executive sponsor. The CDO will work on site with scientific, clinical and technical teams and directly with hospital partners; the role is not a remote data-governance secretariat.

Why this seat is open

Data responsibilities grew around individual programmes and partnership agreements. Capable leaders own clinical data, bioinformatics and platform engineering, but no executive owns their shared definitions, permissions or enterprise value. The pivotal external-control proposal created a clear point of accountability and led the board to establish the CDO seat before regulator engagement is finalised.

What you will own

• Establish a traceable data model connecting patient, specimen, assay, molecular result, treatment, response, outcome and source context across partner institutions.
• Determine fitness for the proposed external-control use, exposing selection, missingness, temporal, treatment and measurement differences before analytic choices are locked.
• Govern consent, privacy, data-use and contractual permissions by purpose, including research, regulatory submission, publication, partner sharing and model development.
• Lead data engineering, stewardship, governance and partnership operations across a wider 280-person and partner perimeter, with named owners for critical definitions.
• Negotiate hospital and laboratory data agreements around update frequency, provenance, corrections, linkage, audit, permitted use, derived data and end-of-term obligations.
• Create data quality measures tied to the decisions each product supports rather than a universal completeness score that hides consequential gaps.
• Integrate clinical-trial and real-world sources where appropriate while preserving source distinctions and preventing convenient post hoc redefinition.
• Build the long-term data investment case, including capabilities to own, specialist services to buy and datasets whose renewal does not justify their scientific or strategic value.

The first 12 months

• Days 1–90: Reconstruct the external-control cohort from source permissions and definitions, quantify site and time differences and stop circulation of unsupported headline estimates. Agree the target question with clinical and statistical leaders, identify evidence gaps requiring regulator discussion and prioritise contract amendments that cannot wait.
• Months 4–9: Implement cohort and lineage controls, common treatment and outcome definitions and site-level quality reporting. Engage regulators with a transparent feasibility package, renegotiate priority partner agreements and establish purpose-based access. Appoint data-product owners who can accept or reject proposed uses against evidence and permission.
• Months 10–12: Deliver a regulator-informed decision on the external-control role, with a reproducible cohort and locked analysis inputs if the route proceeds. Demonstrate reliable updates from priority institutions, publish the enterprise data roadmap and retire duplicate datasets or pipelines that cannot meet defined scientific needs.

What the board will measure

• Reproducibility of the proposed cohort and its key variables from source through transformation, exclusion and final analytic dataset.
• Explicit quantification and treatment of missingness, selection and site or temporal differences, with no material limitation hidden from board or regulator discussions.
• Data use within consent, contract and privacy permission, including controlled derived products, model training, publication and deletion obligations.
• Hospital and laboratory partners meeting provenance, correction and update standards, with unresolved exceptions visible before evidence deadlines.
• Reduction in conflicting definitions and duplicate pipelines for patient, specimen, biomarker, treatment and outcome concepts.
• Data investment concentrated on assets that change portfolio, trial or regulatory decisions, with renewal and build choices supported by observed use and quality.

The person

You are a Chief Data Officer, head of data, real-world evidence leader or senior clinico-genomic executive with 18–22 years in oncology, biotechnology, biopharma, diagnostics or health data. You have created a multi-institution dataset used for a regulatory, clinical-development or similarly consequential decision. You have controlled at least USD 75 million in data and analytics investment and led at least 150 employees and partners.

You understand comparability as more than schema matching. You can interrogate how testing access, panel evolution, treatment choice, follow-up and endpoint ascertainment shape a cohort. You have worked with biostatisticians and clinicians to define an external comparator or real-world endpoint and can explain when the data should not be used despite a compelling preliminary result.

The board requires practical command of data rights. You have negotiated with hospitals, laboratories or networks and know how consent, permitted purpose, derived data, publication and model training differ. You can build stewardship that enables responsible use and does not make every decision wait for a central committee.

The appointment is based on site in San Diego. Candidates from adjacent markets may qualify if they have current US healthcare data, privacy and regulatory experience and will relocate. The ideal leader is scientifically curious, precise about uncertainty and willing to make the business value of data depend on its fitness rather than its volume.

Compensation and terms

The compensation framework provides USD 360,000–480,000 in base salary, an annual incentive and long-term participation. Measures will focus on evidence fitness, provenance, responsible use, partnership reliability and data investment value. This is a permanent new appointment. Relocation and substantiated forfeited awards may be considered within final terms.

Confidentiality

The company, programme, hospital systems, laboratories and cohort findings remain confidential. Identifying detail will be released only after suitability is established and required agreements are signed. Applicants must not query possible data partners or public studies in an attempt to identify the client.

Each response must contain no more than 49 words.