Information Research Scientist

Base pay range

$/yr - $/yr

The Senior Computer & Information Research Scientist leads applied research and innovation for advanced computing, data, and AI techniques that support transformation of HHS’s grants ecosystem, including Grants.gov, Grant Solutions, TAGGS, and One Grants Cloud. This role works closely with enterprise architects, senior technical directors, and product leaders to design and validate novel algorithms, data architectures, and AI‑enabled capabilities that improve scalability, automation, transparency, and user experience for federal grants management.

• Conceive, design, and conduct advanced research in areas such as large‑scale data engineering, AI/ML, optimization, and human‑in‑the‑loop automation tailored to grants lifecycle, compliance, and transparency requirements.
• Develop and refine algorithms, models, and computational methods for use in AI‑powered grants data lakes (e.g., One Grants Cloud), including inference architectures that support predictive analytics, anomaly detection, and intelligent process automation.
• Translate transformation objectives (e.g., OM cost reduction, consolidation, improved usability, responsible AI) into research questions and experimental designs that can be validated via prototypes, pilots, and proof‑of‑concepts.
• Collaborate with enterprise, business, and data architects to align research outputs with target architectures, reference patterns, and modernization roadmaps, ensuring methods are scalable, modular, interoperable, and secure.
• Lead technical investigations on complex systems problems (e.g., performance bottlenecks, data quality issues, multisystem integration challenges) and propose research‑grade solutions that can be operationalized by implementation teams.
• Produce high‑quality technical documentation, research briefs, design specifications, and experiment reports suitable for executive decision‑making, governance boards, and cross‑vendor coordination.
• Mentor junior researchers, data scientists, and analysts; provide technical leadership in AI/ML standards, experimentation practices, code review, and reproducible research workflows.
• Stay current on federal AI policy, trustworthy AI principles, privacy/security guidelines, and emerging technologies; recommend adoption paths and guardrails for use in grants systems.
• Support stakeholder engagement by explaining complex research and AI concepts in clear, nontechnical language to senior leadership, program owners, and partner agencies.

• Ph.D. in computer science, information science, statistics, applied mathematics, or closely related field; or a master’s degree with substantial equivalent research experience in an advanced computing/AI setting.
• Typically 7+ years of postgraduate research experience, including demonstrated contributions to advanced algorithms, AI/ML systems, or large‑scale data platforms (publications, patents, or production deployments highly desirable).
• Deep expertise in at least two of the following domains: machine learning, deep learning, or reinforcement learning; optimization, operations research, or decision science; natural language processing and information retrieval.
• Strong programming skills in languages commonly used for research and production (e.g., Python, Java/Scala, or similar) and familiarity with modern ML/data frameworks (e.g., PyTorch, Tensor Flow, Spark, distributed databases).
• Demonstrated ability to drive research from concept through prototype to handoff for operationalization, including experimental design, evaluation, and performance measurement.
• Excellent written and verbal communication skills, including experience presenting complex findings to nontechnical stakeholders and senior leadership.
• Ability to obtain and maintain any required public‑sector security clearances; experience in regulated or public‑sector environments strongly preferred.

• Experience applying AI/ML or advanced analytics to domains with rigorous compliance and oversight requirements (e.g., federal grants, finance, healthcare, or public‑sector accountability).
• Familiarity with federal AI and data policy (e.g., Federal Data Strategy, trustworthy AI guidelines, privacy/security requirements) and with cloud platforms used in government environments.
• Prior work with large and heterogeneous datasets, including noisy or legacy data, and experience designing robust data quality and monitoring approaches.
• Evidence of thought leadership: peer‑reviewed publications, conference presentations, open‑source contributions, or recognized internal technical leadership roles.

Mid‑Senior level

Full‑time

Research and Analyst

IT Services and IT Consulting

• Medical insurance
• Vision insurance
• 401(k)
• Tuition assistance