Director - Surgical Data Annotation & Programs (Pune)

Role Goal
Provide strategic and operational leadership for a portfolio of high throughput, clinically defensible, audit ready surgical video annotation programs. Own scale, standardization, automation leverage, quality systems, and client trust across multiple programs-ensuring predictable delivery, regulatory readiness, and measurable ROI on human in the loop operations.

What You'll Do
Portfolio & Delivery Ownership (E2E)

Own end to end delivery for multiple concurrent surgical video annotation programs across clients, procedures, and modalities.

Set and enforce standard operating models from intake de identification annotation QA/IRR adjudication dataset release + evidence packs.

Ensure programs meet or exceed SLAs, quality thresholds, and release timelines at scale. Operating Model & Standardization

Define and institutionalize annotation operating standards: o Program playbooks o SOPs o Quality gates o Evidence pack structure o Dataset versioning discipline

Ensure every program is reproducible, auditable, and clinically defensible. Ontology & Clinical Governance

Partner with senior clinical SMEs to: o Define and approve procedure level ontologies (phases, steps, anatomy, tools, events). o Ensure consistent translation into labeling guidelines, UI constraints, and QA checks.

Own governance mechanisms to resolve clinical ambiguity, manage guideline evolution, and prevent ontology drift across programs.

Set the automation vision and roadmap for surgical video labeling: o Pre labeling + verification as default o Confidence/uncertainty based task routing o Active learning feedback loops

Drive continuous reduction in cost per labeled minute and human effort per release.

Partner with ML, platform, and data engineering leaders to productionize automation gains.

Design and govern enterprise grade quality systems: o Multi rater strategies by label class o IRR standards (kappa, alpha, IoU/Dice as applicable) o Calibration and retraining frameworks o Acceptance thresholds by use case (R&D vs regulated)

Ensure every dataset ships with a complete Evidence Pack: o Provenance o QA & IRR reports o Adjudication logs o Clinical and delivery sign offs

Own disagreement governance across programs: o Escalation paths to senior adjudicators and clinicians o Systematic tracking of ambiguity categories o Closure of recurring issues via guideline and tooling updates

Proactively identify delivery, quality, compliance, and reputational risks. Security, Privacy & Compliance Leadership

Ensure all annotation programs comply with: o De identification standards o Data access controls o Logging, retention, and audit requirements Serve as executive owner for security reviews, audits, and vendor risk assessments (SOC2 / ISO aligned environments).

Act as senior escalation and trusted advisor for clients.

Lead executive level program reviews, roadmap discussions, and expansion opportunities.

Ensure PoCs convert into long term, scaled production partnerships.

Build and lead a multi layered delivery organization: o Program Leads o Senior annotators & adjudicators o QA auditors o Training & calibration leads Define career pathways, certification standards, and succession plans.

Enterprise level: o SOP libraries o Training academies o Calibration playbooks o Release governance checklists

Cross program tooling consistency and metrics instrumentation.

Own portfolio level metrics: o Throughput & cycle time o Rework and defect density o IRR trends by label type o Acceptance pass rate o Cost per labeled minute/hour o Automation leverage and pre label acceptance

Translate metrics into decision ready insights for leadership and clients

Direct experience with surgical video data (endoscopy, robotics, OR cameras).

Prior ownership of automation or ML assisted labeling programs at scale.

Experience leading dataset versioning, reproducibility, and audit ready release processes.

Exposure to enterprise security, privacy, and compliance frameworks.

Background in building delivery organizations from early scale to maturity.