Biotech R&D Talent-Portfolio Analytics Director

The mandate

A biotechnology group has stopped two therapeutic programmes and accelerated three computationally enabled candidates. Leaders identify scientists by department and publication record, while the new portfolio needs specific assay, modality, translational, clinical and data-integration capability at different stages. Redeployment discussions are becoming political, and external hiring assumptions ignore learning time. The company needs a fact-based talent portfolio before individual decisions begin.

The twelve-week deliverable is a scientific capability ontology, evidence-backed supply map, programme demand model and redeployment option book. Milestone one defines programme scenarios and roles in week three; milestone two maps capability and proficiency in week six; milestone three models gaps, adjacencies and build-buy-partner choices in week nine; milestone four delivers accepted portfolio decisions, limitations and refresh governance.

The client will provide programme plans, team rosters, project contributions, laboratory responsibilities, methods, clinical and data work, training, publications, patents, performance evidence, vacancies, external partnerships and authorised manager interviews. Acceptance requires capabilities to map to observable programme work, proficiency evidence to exceed self-report, demand to reconcile to approved scenarios and internal analysts to rerun one programme stop and one acceleration case.

The consultants will not select employees for redundancy, judge scientific truth, rank publications, certify laboratory competence, make programme decisions or recruit external talent. Scientific authorities validate capability evidence and executives own portfolio choices. Individual data will be protected, and uncertainty about contribution cannot be converted into a negative employment inference.

Outputs must distinguish domain knowledge, method proficiency, stage experience, collaboration role, learning adjacency and leadership of scientific judgment. Headcount cannot substitute for scarce capability. Individual staffing, employment consultation, search execution and analytics-platform implementation after acceptance remain outside this engagement.

Why this is external work

Scientific leaders understand programmes but naturally advocate for their teams, while HR systems carry broad job families rather than current capability. Internal analytics lacks specialist capacity during reprioritisation. External talent-portfolio work can establish comparable evidence and options without making scientific or employment decisions.

What you will own

• Translate pipeline scenarios into modality, method, stage, regulatory, data and collaboration capability demand.
• Map employee and partner supply through observed programme contribution, proficiency, recency and independent-use evidence.
• Identify scarce capability, single-person dependency, underused depth, learning adjacency and external supply constraints.
• Model redeploy, reskill, recruit, partner, sequence and stop-work options with time and programme consequence.
• Protect individual data and separate missing contribution evidence from negative capability or performance judgment.
• Create refresh controls connecting programme decisions, assignments, learning, departures and new scientific evidence.
• Deliver the accepted ontology, supply map, demand engine, gap scenarios, redeployment options and trained internal analyst routines.

Candidate qualifications

• Led scientific workforce analytics for complex biotechnology or pharmaceutical pipeline reprioritisation across multiple therapeutic modalities.
• Mapped capability from actual programme and laboratory contribution rather than title, publication count or self-report.
• Modelled learning adjacency, realistic redeployment time and external partner supply under programme stop and acceleration scenarios.
• Worked with scientific authorities without judging research validity or certifying technical competence.
• Protected individual inference during politically sensitive workforce planning and potential role reduction.
• Transferred usable capability models, protected data and refresh governance to internal people analytics teams.

Non-negotiables

• Can complete six Boston, Cambridge, Basel or San Diego scientific workshops within twelve weeks.
• Will disclose biotech employer, investor, search, laboratory partner and workforce-platform relationships.
• Brings pipeline-linked scientific talent analytics; generic skills inventory or bibliometrics is insufficient.
• Accepts no authority over programme choice, scientific truth, competence certification, staffing or redundancy.

1. 49 words maximum. Describe a scientist whose transferable capability was invisible in job title or publication record.
2. 49 words maximum. Which evidence would support redeployment from a stopped programme to a different modality?
3. 49 words maximum. How would you protect employees when contribution data is incomplete during reprioritisation?