Computational Finance Scientist

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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 Analysis Innovation Center. In FINLab, our CompFi scientists provide expert analysis and consulting to our Federal Government clients in transforming their technologic and regulatory processes to enhance the safety, stability, and security of the US Banking System, Financial Markets, and supporting economic infrastructure. Join a highly skilled team executing research, performing analyses, and advising multiple stakeholders. These studies of national significance will be executed in collaboration with industry, academic, and governmental experts and stakeholders. This provides us with unprecedented access to expertise, ideas, and data. You will be a critical Finance subject matter expert (SME) as part of a growing, agile, multidisciplinary team working with academics, the Financial Sector, and US Financial Regulators.

This is a unique position. Competitive applicants will have demonstrated expertise in at least two of the following areas: Financial Market Microstructure and Regulation, Fintech, Regulatory Tech and Supervisory Tech, Financial Analytics, Market Modeling and Analysis. However, an applicant's expertise in these areas should be premised upon leveraging complexity science to create unique insights into market dynamics as emergent phenomena that are part of a greater complex (in the formal scientific sense) economic system. Furthermore, FINLab leverages a multidisciplinary approach to financial and economic systems analysis. As such, successful candidates will bring that perspective to the position via previous analytic work in related fields, for example a complexity science analysis of socioeconomic or political systems.

This position is not specifically forensic in nature. Rather, FINLab and the associated team take the perspective that the economy is a complex adaptive system, and as such is nonstationary. Historical analysis will only get us so far, we also need to employ tools and techniques, e.g., agent-based computational economics, that allow us to explore the generative mechanisms that underlie markets and market dynamics.

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:

• Requires 8 years of experience and a Masters degree or 7 years with a PhD, with published research in computational finance, complexity economics or quantitative finance, broadly defined.
• Very strong academic credentials in quantitative or computational finance with experience in the simulation of equity market dynamics.
• Experienced researcher as evidenced by a peer reviewed publication record with associated H-index of 10 or more.
• Ability to bridge finance, computational, and data analytic domains.
• Thrives in 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.
• Excellent interpersonal skills, and effective working relationships with internal and external customers.
• Demonstrated experience working on or leading customer facing engagements emphasizing quantitative or computational finance.
• Demonstrated ability to manipulate large financial datasets and time series data and perform calculations and create visualizations with at least one modern programming language like Python (utilizing packages like scikit-learn, pandas, or dask), R (utilizing packages like caret, dplyr, or data.table), or other modern programming language.
• Ability to apply, modify and formulate algorithms and processes to solve computational financial problems.
• Desire and ability to obtain and hold a DoD Secret clearance.
• This position requires a minimum of 50% hybrid on-site
• Per the U.S. Government's eligibility requirements, you must be a U.S Citizen to be considered for a security 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 as evidenced by scientific publication.
• Research experience with the global financial system.
• Experience leading teams in a technical environment and delivering meaningful impacts in computational finance, as measured by securing and managing extramural funding in excess of one million dollars.
• Experience with building and shaping research programs via successful competition for extramural funding in excess of one million dollars.
• 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.
• Familiarity working in cloud-based computing environments like Amazon Web Services, Google Cloud, or Microsoft Azure.
• 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).

This requisition requires the candidate to have a minimum of the following clearance(s):

Secret

This requisition requires the hired candidate to have or obtain, within one year from the date of hire, the following clearance(s):

Secret

Salary compensation range and midpoint:

$173,200 - $216,500 - $259,800 Annual

Work Location Type:

Hybrid

Commitment to Non-Discrimination

All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, local or international law.

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