Principal Scientist, Differential Privacy in United States at Jobgether
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Job Description
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Principal Scientist, Differential Privacy in the United States.
This is a senior technical leadership role at the forefront of privacy engineering and differential privacy research, supporting national-level efforts to advance how sensitive data is safely shared, analyzed, and evaluated. You will lead the design and execution of cutting-edge privacy-enhancing technologies, including privacy-preserving record linkage, synthetic data evaluation, and differentially private data access frameworks. The role combines deep research expertise with hands-on technical direction, guiding multidisciplinary work across multiple task areas while shaping publicly released methodologies and standards. You will be responsible for defining rigorous privacy and utility metrics that inform real-world data protection practices. Acting as the primary technical liaison with key stakeholders, you will ensure research outputs are reproducible, transparent, and applicable in practice. This position sits at the intersection of advanced research, applied mathematics, and national-scale privacy innovation in a highly collaborative environment.
- Provide end-to-end technical leadership across all research and development workstreams, including privacy-preserving record linkage, synthetic data evaluation, and de-identification methodologies.
- Lead the design, authorship, and publication of technical reports defining trust models, taxonomies, metrics, and evaluation frameworks for privacy-enhancing technologies.
- Define and formalize advanced metrics for assessing data utility, fidelity, and empirical privacy guarantees in de-identified and synthetic datasets.
- Oversee the implementation and configuration of open-source tools and demonstration environments for privacy-preserving data analysis use cases.
- Coordinate subject-matter expert (SME) review panels and integrate expert feedback into technical deliverables and research outputs.
- Serve as the primary technical liaison with external stakeholders, ensuring alignment, clarity, and scientific rigor across all deliverables.
- Represent research findings at conferences, workshops, and technical forums, contributing to the broader scientific community.
- Ph.D. in Computer Science, Applied Mathematics, or a closely related field with a focus on differential privacy or privacy-preserving systems (or equivalent experience).
- 10+ years of experience in privacy-preserving algorithms, differential privacy, or related advanced data protection research.
- Strong applied mathematics and algorithmic background, including experience solving complex optimization problems.
- Proven track record of leading or significantly contributing to privacy-preserving data systems, benchmarks, or evaluation frameworks.
- Experience designing and deploying demonstration systems for privacy-preserving data sharing or analysis.
- Demonstrated publication record, including peer-reviewed papers, technical reports, and invited talks.
- Strong communication skills with the ability to translate complex technical concepts into clear, structured documentation.
- Experience collaborating with multidisciplinary research teams and external expert stakeholders.
- Competitive compensation with a negotiable salary aligned to experience and expertise.
- Comprehensive health coverage including medical, dental, and vision insurance.
- Short-term and long-term disability coverage plus life insurance.
- 401(k) retirement savings plan.
- Paid time off and paid holidays.
- Remote-first full-time work structure with standard weekday schedule.
- Professional development opportunities within a research-driven, high-impact environment.
- Inclusive and collaborative workplace culture supporting long-term career growth.