Jobs · Information Technology · Virginia

Lead Computational Finance Scientist

MITRE · McLean, VA · 2 mo ago
Information Technology$157k–$196k/yrFull-time

Department Summary

MITRE is currently seeking motivated and qualified applicants for a Computational Finance (CompFi) Scientist to join our Financial Innovation Laboratory (FINLab) and Model-Based Analytics Department (L144) in the Modeling and Simulation Innovation Center.

Roles & Responsibilities

  • Develop innovative, multidisciplinary approaches for analyzing financial data and trends that may impact the US financial system and markets
  • Provide expert analysis and/or develop research proposals on issues related to improving financial regulation and banking supervision, adopting new technologies to support distributed ledger or faster payments, or implementing advanced financial analytics
  • Understand US, mission partner, and adversary capabilities and assess potential threats to U.S. financial stability and security
  • Conduct analytic and simulation-based analyses using financial data to provide new insights which support policy-level decision making
  • Provide US Treasury and related sponsors with commercial and market analysis of national interest areas, and methodologies to identify mitigation alternatives

Basic Qualifications

  • Typically requires a minimum of 8 years of related experience with a Bachelor’s degree; or 6 years and a Master’s degree; or a PhD with 3 years of experience; or equivalent combination of related education and work experience.
  • Very strong academic credentials in quantitative or computational finance.
  • Experienced researcher as evidenced by a peer reviewed publication record.
  • Experience and expertise in financial analysis and market modeling.
  • Experience in designing and executing impactful research.
  • Ability to bridge finance, computational, and data analytic domains.
  • Experience working in a technical environment with multidisciplinary teams on critical national security challenges.
  • Passion for developing new technology and analytics for solving national challenges.
  • Excellent analytic writing and verbal/presentation skills to senior leaders.
  • Experience or familiarity with visualizing multi-dimensional financial data or events, using tools such as Tableau, Plotly, ggplot2, matplotlib, seaborn, or D3.js.
  • Demonstrated ability to manipulate large financial datasets and time series data and perform calculations with at least one modern programming language, e.g., Python (utilizing packages like scikit-learn, pandas, or dask), R (utilizing packages like caret, dplyr, or data.table), or other modern language.
  • Ability to apply, modify and formulate algorithms and processes to solve computational financial problems.
  • Ability to obtain and maintain Top Secret clearance.

Preferred Qualifications

  • PhD in a quantitative discipline, with deep knowledge of financial markets and market dynamics.
  • Experience with U.S. Treasury, Financial Regulators, or with the commercial side such as the Banking or Finance Industry.
  • Experience performing novel market research and analyses. Scientific publication is expected.
  • Research experience with the global financial system.
  • Ability to bridge finance, computational, economics, and data analytic domains. While this position is centered upon financial systems and their dynamics, the ideal candidate will bring a multidisciplinary perspective, in terms of tools and techniques, to this that includes complex systems, complexity economics, or ergodic economics.
  • Experience applying various machine learning approaches (e.g., random forest, neural networks, support vector machines).
  • Experience working with databases (e.g., PostgreSQL, Oracle, MySQL, MongoDB, Neo4J).
  • Experience using version control (e.g., Git, Mercurial, SVN) to support collaborative development.
  • Experience utilizing notebooks (e.g., Jupyter, R Markdown, Zeppelin). Experience developing interactive data visualizations using open-source technologies (e.g., Angular, Vue, React, D3.js) or other frameworks (e.g., Shiny).

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