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Research Facilitator

Job in Kansas City, Jackson County, Missouri, 64101, USA
Listing for: Federal Reserve Bank of New York
Full Time position
Listed on 2026-10-12
Job specializations:
  • IT/Tech
    Data Scientist
  • Research/Development
    Data Scientist
Salary/Wage Range or Industry Benchmark: 91600 - 181500 USD Yearly USD 91600.00 181500.00 YEAR
Job Description & How to Apply Below

Company Federal Reserve Bank of Kansas City

When you join the Federal Reserve—the nation's central bank—you’ll play a key role, collaborating with leading professionals to strengthen and protect our economic, financial and payments systems. We invest in contemporary and emerging technology each year to support the Federal Reserve and our economy, and we’re building a dynamic and diverse team for our future. As a research facilitator you will engage with economists and research associates in the use of state-of-the-art computational systems, tools, and software to enable research productivity.

Partner with researchers to co-create and co-learn relevant computing and data capabilities. Reduce barriers to utilizing High Performance Computing (HPC) instruments for innovative and computationally complex economic research. Accelerate time-to-publication through software optimization, parallelization, and modern computational techniques.

Key Activities Researcher Engagement
  • Provide direct support to economists and research associates through consultations.
  • Build deep understanding of economic research activities and computational requirements.
  • Co‑author research papers under the guidance of economists.
Solutions Development
  • Facilitate design, debugging, and optimization of research workflows and software models alongside researchers.
  • Implement software parallelization and performance improvements to reduce time to publication.
  • Support adoption of cloud computing and AI tools, including large language models, in research workflows.
Partnership/Collaboration
  • Facilitate economist usage of on‑prem and cloud HPC environments.
  • Communicate regularly with research staff and technical professionals.
  • Collaborate across teams on computational approaches and best practices.
Documentation/Training
  • Develop and deliver curriculum on research computing tools and techniques including:
    Version control (Git/Git Lab), Programming languages (Python, R, Matlab, C, Stata, SQL), Linux command line and terminal usage, High Performance Computing and job scheduling (e.g. SLURM), AI/LLM utilization and cloud computing.
  • Provide one‑on‑one consultations and maintain documentation of local computing resources.
  • Give presentations to research staff on latest tools and techniques.
Basic Qualifications
  • Bachelor’s degree in a computational field (Computer Science, Computational Economics, Applied Mathematics, Data Science, or related field).
  • Minimum of 5 years’ relevant post‑secondary education OR relevant work experience including a combination of these two.
  • Proficiency in multiple programming and scripting languages (Python, R, Matlab, C, Stata, SQL, or equivalent).
  • Knowledge of AI tools and practical experience utilizing large language models for research applications.
  • Strong communication skills with ability to translate complex technical concepts for research audiences with varying levels of programming experience.
  • Experience with command line tools and Linux operating systems.
  • Demonstrated ability to work collaboratively with researchers from diverse backgrounds.
  • Service‑oriented mindset with commitment to supporting research excellence.
  • Experience with version control systems (Git/Git Lab).
  • Terminal proficiency and Linux system navigation.
Preferred Qualifications
  • Master’s degree in a computational field.
  • Experience with High Performance Computing environments and job schedulers (Slurm or equivalent).
  • Background in economic research or working with economists.
  • Prior research experience in academic or policy research settings.
  • Experience with parallel computing and code optimization techniques.
  • Experience supporting GPU‑accelerated research computing, including adapting existing workflows to leverage GPU resources.
  • Familiarity with research workflows…
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