Lead Data Scientist: Differential Privacy for QOZ Analytics

E Logic; Richmond (VA); Remote; USD 24,000 - 40,000; Part time

Job summary

E-Logic, Inc. seeks a Lead Data Analyst/Data Scientist specializing in differential privacy to support IRS SOI on QOZ statistics.

The role focuses on developing and evaluating privacy-preserving methodologies, conducting privacy-utility analyses, and guiding synthetic data and statistical modeling efforts. The candidate will lead technical work, ensure compliance with federal data governance, and collaborate with stakeholders across data engineering, policy, and IT.

Qualifications

• Proven experience applying differential privacy in Python and privacy-preserving analytics.
• Experience with statistical disclosure limitation and secure data aggregation.
• Familiarity with federal data handling standards (Privacy Act, FISMA, OMB).
• Ability to develop technical documentation and training materials.

Responsibilities

• Develop and evaluate differential privacy methods for QOZ statistics.
• Balance privacy protection with statistical utility in models and outputs.
• Support production pipelines and documentation for government reporting.
• Provide training and knowledge transfer to SOI analysts and data scientists.

Skills

Differential privacy

Python

Statistical modeling

Data analysis

Privacy budgets

Documentation

Tools

Tumult Analytics

Job description

E-Logic, Inc. seeks a Lead Data Analyst/Data Scientist specializing in differential privacy to support IRS SOI on QOZ statistics.

The role focuses on developing and evaluating privacy-preserving methodologies, conducting privacy-utility analyses, and guiding synthetic data and statistical modeling efforts. The candidate will lead technical work, ensure compliance with federal data governance, and collaborate with stakeholders across data engineering, policy, and IT.