Privacy Operations Lead (Quant + Research-Driven)
Company: Integral Privacy Technologies
Location: San Francisco, CA (M–Th in-office)
Team: Customer Solutions (Privacy Ops)
Work Authorization: Must be authorized to work in the United States without requiring sponsorship
About Integral: Healthcare data is among the most valuable, expansive, and regulated data in the world—spanning voice interactions, raw images, clinical notes, financial profiles, and more. This data underpins population health outcomes, research, reimbursement, and increasingly AI. But today’s manual systems to process, optimize, and deploy this data are broken.
Integral provides the missing data operations layer for healthcare. Our Agentic Data Operations Platform streamlines the full set of operations required to make healthcare data usable—from sourcing and compliance to governance and continuous delivery. Instead of relying on fragmented services and bespoke pipelines, enterprises use Integral to manage healthcare data end-to-end through a single, persistent platform.
About the Role: We’re looking for a Privacy Operations Lead to operationalize privacy and compliance across customer implementations and ongoing delivery—while also bringing quantitative rigor to privacy risk assessment and controls design.
You’ll translate privacy requirements into measurable controls, repeatable playbooks, and auditable evidence, and you’ll help Integral advance its privacy methodology by incorporating statistical analyses, de-identification evaluation, and research-informed best practices. This role thrives in ambiguity: you’ll bring structure, judgment, and forward momentum across technical and compliance constraints.
What You'll Do:
Research, Writing, and Methodology Development
- Stay current with academic literature, industry standards, and regulatory guidance related to de-identification, privacy risk, and healthcare data governance
- Research emerging re-identification risks and privacy-preserving technologies; translate findings into practical improvements to methodology and tooling
- Produce crisp written artifacts: internal standards, customer-facing summaries, control narratives, data flow documentation, and assessment memos that stand up to scrutiny
- Create tight feedback loops with Product and Engineering to improve platform capabilities based on real implementation learnings and research insights
Privacy Controls, Governance, and Delivery Enablement
- Own privacy and governance workstreams across implementations and steady-state delivery—embedding requirements into project plans, configurations, and operating procedures
- Translate privacy + regulatory requirements into executable workflows and control narratives (documentation, approvals, monitoring, evidence collection)
- Build scalable playbooks and tooling: privacy checklists, review templates, control libraries, runbooks, and “how we implement safely” standards
- Define and operationalize data intake + use controls: how data is requested, reviewed, approved, accessed, retained, and continuously monitored
- Identify risks early (process, platform, data quality, stakeholder) and design mitigations that keep delivery on track
Quantitative Privacy Analysis and Risk Assessment
- Conduct and/or guide statistical assessments of health datasets to evaluate privacy risk (e.g., uniqueness, linkage risk indicators, small cell risk, release constraint design)
- Help define measurement frameworks for privacy controls (KPIs, thresholds, monitoring checks, evidence completeness, exception tracking)
- Support privacy readiness for audits/assessments by generating audit-ready quantitative summaries and defensible documentation of controls and outcomes
- Partner with engineering and solutions to automate repeatable privacy analyses and risk assessment components (lightweight scripting/SQL/Excel automation)
What We're Looking For
- 2–5+ years of experience in privacy operations, compliance ops, implementation/engagement management, technical program management, consulting, informatics, or adjacent roles
- Demonstrated ability to operationalize privacy/compliance requirements into practical execution (policy interpretation → controls → evidence)
- Quantitative comfort: experience using statistics and structured analysis to evaluate dataset risk, quality, or compliance (health data preferred)
- Strong writing skills: can produce clear, structured documentation and memos with an academic / evidence-based tone
- Familiarity with regulated healthcare data workflows and documentation rigor (auditability, traceability, change control)
- Technical aptitude: comfortable working alongside data/engineering teams; familiarity with pipelines, cloud/on-prem contexts, and clinical data concepts
- Proficiency in Excel; bonus if you build lightweight automations (SQL, scripting, tooling) to streamline repeatable workflows
- Organized and execution-oriented—able to run multiple workstreams with ambiguity and shifting constraints
- Ownership mentality: proactively identify gaps, build processes, and drive adoption
Nice to Have
- Experience with HIPAA concepts, de-identification approaches, or privacy risk assessment methodologies
- Familiarity with privacy-preserving technologies or governance models for AI/ML data workflows
- Experience with data infrastructure or analytics tooling (SQL/Tableau/R/Python)
- EHR/clinical data familiarity (ICD-10/CPT concepts, coding constraints, data quality issues)
- Experience drafting external-facing submissions, comment letters, or regulatory analyses
Why Integral
- Competitive salary commensurate with experience
- Meaningful equity in a high-growth healthcare technology company
- Comprehensive health, dental, and vision insurance
- Daily company-provided lunches
- Monthly wellness reimbursement
- Quarterly team off sites and semi-annual full company offsite
- Professional development opportunities and conference attendance
Expected Salary Range / Equity: $120,000 - $160,000 • 0.05% - 0.1%
Integral is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.