careers

Employees

FORT seeks creative, intelligent, self-aware and numerate colleagues who are curious about global financial markets and investing. Successful employees often have educational degrees in mathematics, computer science, and economics; advanced degrees and STEM backgrounds are not a prerequisite to employment. FORT’s diverse workforce includes people from around the world with extraordinary practical experience as well as extraordinary academic credentials, tied together by common interest in compounding for clients and working in a friendly but challenging environment that mixes individual and team achievement.

Culture

FORT is committed to fostering a culture of diversity and inclusion. The collective sum of the individual differences and life experiences of FORT’s employees is a valuable component of our culture, reputation, and achievements. Our goal is to bring together the best and the brightest in a dynamic environment that inspires high performance, innovation and welcomes diverse views.

What We Look for

Smart

Creative

Team-oriented

Effective communication skills

Self-motivated, can-do attitude

High level of ownership

Ability to prioritize and focus on multiple tasks

Ability to handle diverse, challenging assignments

What We offer

Competitive
compensation and
bonus package

Attractive
benefits plans and
paid time off

Flexibility
for work /
life balance

Professional
learning and
development
opportunities

Opportunities

Data Engineer

Chevy Chase, MD / New York, NY

Data Scientist / Statistician

Chevy Chase, MD

Quantitative Equity Researcher

Chevy Chase, MD / New York, NY

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Data Engineer

Firm Overview

Job Summary

The Data Engineer will participate in all data related efforts within FORT. This position is responsible for generating and maintaining financial metrics used for portfolio and risk analysis, as well as designing, building and maintaining applications that streamline the delivery of mission critical market and modelling data to FORT’s trading systems, modelling systems, portfolio risk analysis and researchers. FORT’s trading systems utilize low latency streaming market data and normalized market data from disparate sources to support automated and algorithmic trading.

Summary of essential job functions

Code data cleaning processes to analyze incoming financial data for absurd and statistically improbably data patterns and automate healing of this data
Provide 24/5 production support for data related applications
Monitor data process output and proactively identify data pipeline failures
Meet with current and prospective data vendors
Assist quantitative researchers in evaluating data quality
Act as a translator between quantitative research, trading, and technology functions, ensuring the continued success and growth of FORT’s investing program.

Minimum Requirements

BS/MS in Computer Science, Engineering or a related field
Experience in Python, R or Julia, C# or Java, and SQL
Experience in functional programming, data cleaning, unit testing and domain driven design
Working knowledge of data modeling and financial markets
Exposure to equity or futures markets
Basic understanding of global market structure
Ability to clearly and effectively communicate and articulate ideas

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Apply for Position

Data Scientist / Statistician

Firm Overview

Job Summary

The Data Scientist/Statistician is responsible for quantitative analysis of financial data; collecting and distilling rich research datasets from varied sources; and in depth analysis of data to aide and support FORT’s systematic investment programs.

Summary of essential job functions

Collection, cleaning and normalization of structured and unstructured financial data into meaningful and high quality data.
Define problem statement and design studies to identify most important aspects of data.
Creative application of data preparation and data analysis skills to iteratively identify hidden facets of data.
Presentation of research findings, recommendations and conclusions along with visual representation of results for wider consumption.
Represent the team to key internal stakeholders while collaborating with the wider research unit and multidisciplinary teams.
Contribute to the development of best practices, improve quality, efficiency and effectiveness.
Translate high-level projects into technical tasks.

Minimum Requirements

Bachelor’s Degree; advanced degree preferred in Statistics, Applied Mathematics, Finance, Economics, Engineering or a related field
Strong academic background
Strong analytical and quantitative skills
Fluency in one or more of the statistical programming languages: R, STATA, Python and SAS
Working knowledge of one or more of the following programming languages: C, C++, C#, Python, and JAVA
Aptitude in critical thinking and problem solving
Excellent verbal, written and interpersonal communication skills, including an ability to translate statistical methods and findings for a non-technical audience
Demonstrated organizational and time management skills
Demonstrated ability to work independently, with limited supervision in a fast-paced environment

Apply

Apply for Position

Quantitative Equity Researcher

Firm Overview

FORT is a hedge fund with $5 billion in AUM, located in metro Washington, DC and New York City. Founded in 1993, the firm develops and implements proprietary, fully automated, systematic trading strategies in global equity, rates, FX and commodity markets. Most of the firm’s activity is over medium and long-term investment horizons based on a variety of fundamental and price data leveraging different quantitative and AI techniques. The bulk of the firm’s assets are employed in global macro strategies using liquid futures markets as the primary trading instrument. A growing part of FORT’s business is a single stock equity strategy, Equity Market Neutral (EMN).

Job Summary

The quantitative equity research role involves developing new alpha strategies and improving the current suite of existing FORT equity signals. The role includes collaboration and close coordination with senior quantitative equity research staff members and working with other groups, including the office of the CIO (OCIO) for portfolio validation and implementation, as well as with performance and risk analytics, software development and business development teams. This important research role combines hands-on coding and statistical evaluation with team interaction and working closely with other research staff members.

Summary of essential job functions

Conduct quantitative research on proprietary risk factor models for equities for both fundamental and quant equity long-short strategies.
Responsible for model evaluation process, including factor selection/recognition, factor return estimation, covariance estimation, idiosyncratic volatility estimation etc.
Conduct research in stress scenarios; build individual equity stress scenario evaluation models and provide full coverage for the equity long-short strategies.
Develop, test and maintain applications to evaluate systematic trading strategies.
Develop and test new risk/alpha factors and new data sources.
Collection, cleaning and normalization of structured and unstructured financial data into meaningful and high quality data.
Integrate multiple data sources in model building.
Develop hypotheses regarding performance of securities and markets based on traditional and alternative data.
Presentation of research findings, recommendations and conclusions along with visual representation of results for wider consumption.
Work with various teams to aggregate information from a variety of sources to create detailed and accurate reports representing the risk and portfolio construction of FORT investment portfolios.
Work closely with Risk Managers, Portfolio Managers and Analysts to understand and incorporate risk metrics and methodologies within the investment process.
Perform various projects involving more generalized investment research to support FORT marketing efforts.

Minimum Requirements

Quantitative advanced degree such as a MS or Ph.D. (preferred) in Finance, Financial Engineering, Machine Learning, Statistics or a related field,
7-12 years of prior relevant, industry experience with financial data and/or quantitative equity research (factor modeling, portfolio construction, risk modeling, machine learning and natural language processing)
Advanced programming knowledge in one or more of the following languages: Python, R, SQL
Superior verbal, written and interpersonal communication skills
Aptitude in critical thinking and problem solving
Demonstrated organizational and time management skills
Demonstrated ability to work independently, with limited supervision in a fast-paced environment

Apply