Technical Project Lead, Data Privacy

Protege • New York, NY

11d

About The Position

Protege is building a platform for the secure, efficient, and privacy-centric exchange of AI training data. The company is a lean, fast-moving team focused on enabling access to high-quality data for AI.

The Technical Project Lead, Data Privacy will lead healthcare data privacy engagements from initial dataset assessment through certified delivery. The role combines off-the-shelf tools, custom rules, language models, and human review, tailoring the approach to each dataset while validating results to standards accepted by independent expert reviewers and auditors. The position will make decisions about what data is safe to deliver and continuously improve the privacy method based on engagement findings.

The role works directly with independent expert determiners, directs human reviewers on difficult cases, evaluates tools and models, and documents learnings for future engagements. Success includes learning the method and delivering an intake assessment in the first 30 days, co-leading an engagement and owning pipeline experiments by 60 days, and leading an engagement end to end—including its expert-review evidence package—by 90 days.

Requirements

• At least 2 years of experience in data science, applied statistics, ML engineering, or quantitative research, working with real, messy data.
• Strong statistical skills, including sampling, confidence intervals, measurement design, and inter-rater agreement; ability to explain sample adequacy and limitations.
• Strong background and experience using language models or AI coding tools to work quickly.
• Healthy skepticism and willingness to verify claims before trusting them, including one's own.
• Clear writing for technical and non-technical audiences, including external reviewers.
• Authorization to work in the U.S. as a W2 employee, required for access to protected health information.

Nice To Haves

• Experience with HIPAA de-identification (Safe Harbor or expert determination), or other privacy or healthcare data work.
• Experience with NER, OCR, clinical NLP, or document processing.
• Experience working with auditors, regulators, or external reviewers.
• Experience running annotation or labeling projects.

Responsibilities

• Lead data privacy projects from initial dataset review through certified delivery, including assessment, policy writing, pipeline tuning, validation, and delivery.
• Design and run experiments to determine which processing layers a dataset needs, measuring recall, over-redaction, and cost.
• Conduct auditor-style validation by setting pass thresholds in advance, testing on fresh held-out samples, reporting confidence bounds, and keeping test sets unchanged.
• Convert every identified miss into a lasting corrective action, such as a rule, model or prompt change, or human-review step, and add a regression test.
• Work with independent expert determiners by preparing evidence, answering methodology questions, and responding to findings.
• Direct human reviewers on difficult cases and adjudicate disagreements.
• Evaluate new tools and models, including open-source NER, vendor APIs, and models running in a partner's environment, against company benchmarks.
• Document findings and lessons so future engagements can build on prior work.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed