The Role
Monitor systematic trading strategies and identify portfolio and operational risks. Investigate anomalies, coordinate root-cause resolution with trading, modeling, and engineering teams, and perform statistical analysis of strategy behavior. Build Python-based analytical tools, dashboards, alerts, automated workflows, and reporting systems. Maintain data profiling platforms, test code, troubleshoot Linux-based processes, document risk procedures, and communicate findings to investment and investor-facing stakeholders.
Summary Generated by Built In
Position Summary
DUTIES: Develop a deep understanding of Two Sigma's systematic modeling and trading platforms and the global equity and derivatives markets they operate in. Monitor daily trading strategy behavior and proactively identify issues that may present risks to Two Sigma's investors and portfolios, including participating in the team's Risk Support Rotation responsible for escalating issues in real-time to trading businesses, portfolio managers, and engineering and modeling partners. Lead root-cause investigations into trading strategy behavior anomalies and operational issues, coordinating with engineering, modeling, and trading partners to resolve them. Build and use tools for quantitative trading strategy analysis using Python. Perform statistical analysis including regression, correlation, and other quantitative methods to evaluate systematic strategy behavior and risk exposures. Prepare, review, and present reports on systematic strategy behavior and risk to stakeholders including portfolio managers and investor-facing teams. Gather requirements from multiple partner teams and design, implement, and test new metrics, dashboards, and analytical tools for the Risk department. Develop and maintain automated alerts, sanity checks, and reporting systems for the Risk department and its partners. Maintain and enhance key data profiling and alert generation platforms, working with large codebases and implementing unit and integration testing to ensure code reliability. Review and trace through code to troubleshoot issues and implement test cases for code validation. Develop scripts and automated workflows for strategy access control and operational risk processes, working within a Linux environment using command-line tools for file operations, process management, and data processing. Perform, document, and improve operational Risk processes, with an eye towards automation, including writing clear technical documentation, runbooks, and process guides. Collaborate regularly with modelers, portfolio managers, traders, and investor-facing teams on cross-functional initiatives to improve risk management capabilities.
Minimum Requirements:
Bachelor's degree or the equivalent in Computer Science, Applied Mathematics, Computational Finance and Risk Management, or related field plus 1 year of experience in finance, operational risk management, software engineering or related experience. Must have experience with developing, maintaining & troubleshooting codebases, including code review & implementing test cases for code validation. Must have experience with programming in Python, including numerical & data analysis libraries (Pandas, Numpy) for quantitative analysis. Must have experience with querying, manipulating & managing data using database tools, including processing & profiling large datasets from multiple sources, data cleaning, quality checking & validation. Must have experience with applying statistical analysis methods including regression, correlation & other quantitative methods for evaluating strategy behavior & operational risks. Must have experience with operating in Linux environments, including basic commands for file operations, process management, text search & data processing. Must have experience with designing & building automated tools, alerts & analytical reporting for data-driven decision-making. Must have experience with monitoring operational processes & system outputs, identifying & escalating anomalies or issues. Must have experience with preparing technical documentation, research reports & analytical findings & collaborating with cross-functional teams including investment, engineering & operations stakeholders. Must have experience with conducting root-cause investigations of operational issues. Must pass company's required skills assessment. Employer will accept any amount of experience with the required skills.
Rate of pay: The base pay for this role will be between $150,000 and $200,000 per year. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental and other wellness plans and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications and experience.
#LI-DNI
DUTIES: Develop a deep understanding of Two Sigma's systematic modeling and trading platforms and the global equity and derivatives markets they operate in. Monitor daily trading strategy behavior and proactively identify issues that may present risks to Two Sigma's investors and portfolios, including participating in the team's Risk Support Rotation responsible for escalating issues in real-time to trading businesses, portfolio managers, and engineering and modeling partners. Lead root-cause investigations into trading strategy behavior anomalies and operational issues, coordinating with engineering, modeling, and trading partners to resolve them. Build and use tools for quantitative trading strategy analysis using Python. Perform statistical analysis including regression, correlation, and other quantitative methods to evaluate systematic strategy behavior and risk exposures. Prepare, review, and present reports on systematic strategy behavior and risk to stakeholders including portfolio managers and investor-facing teams. Gather requirements from multiple partner teams and design, implement, and test new metrics, dashboards, and analytical tools for the Risk department. Develop and maintain automated alerts, sanity checks, and reporting systems for the Risk department and its partners. Maintain and enhance key data profiling and alert generation platforms, working with large codebases and implementing unit and integration testing to ensure code reliability. Review and trace through code to troubleshoot issues and implement test cases for code validation. Develop scripts and automated workflows for strategy access control and operational risk processes, working within a Linux environment using command-line tools for file operations, process management, and data processing. Perform, document, and improve operational Risk processes, with an eye towards automation, including writing clear technical documentation, runbooks, and process guides. Collaborate regularly with modelers, portfolio managers, traders, and investor-facing teams on cross-functional initiatives to improve risk management capabilities.
Minimum Requirements:
Bachelor's degree or the equivalent in Computer Science, Applied Mathematics, Computational Finance and Risk Management, or related field plus 1 year of experience in finance, operational risk management, software engineering or related experience. Must have experience with developing, maintaining & troubleshooting codebases, including code review & implementing test cases for code validation. Must have experience with programming in Python, including numerical & data analysis libraries (Pandas, Numpy) for quantitative analysis. Must have experience with querying, manipulating & managing data using database tools, including processing & profiling large datasets from multiple sources, data cleaning, quality checking & validation. Must have experience with applying statistical analysis methods including regression, correlation & other quantitative methods for evaluating strategy behavior & operational risks. Must have experience with operating in Linux environments, including basic commands for file operations, process management, text search & data processing. Must have experience with designing & building automated tools, alerts & analytical reporting for data-driven decision-making. Must have experience with monitoring operational processes & system outputs, identifying & escalating anomalies or issues. Must have experience with preparing technical documentation, research reports & analytical findings & collaborating with cross-functional teams including investment, engineering & operations stakeholders. Must have experience with conducting root-cause investigations of operational issues. Must pass company's required skills assessment. Employer will accept any amount of experience with the required skills.
Rate of pay: The base pay for this role will be between $150,000 and $200,000 per year. This role may also be eligible for other forms of compensation and benefits, such as a discretionary bonus, health, dental and other wellness plans and 401(k) contributions. Discretionary bonus can be a significant portion of total compensation. Actual compensation for successful candidates will be carefully determined based on a number of factors, including their skills, qualifications and experience.
#LI-DNI
Skills Required
- Bachelor's degree or equivalent in Computer Science, Applied Mathematics, Computational Finance and Risk Management, or a related field
- At least 1 year of experience in finance, operational risk management, software engineering, or related experience
- Experience developing, maintaining, and troubleshooting codebases, including code review and implementing test cases
- Experience programming in Python, including Pandas and NumPy for quantitative analysis
- Experience querying, manipulating, and managing data using database tools, including processing and profiling large datasets
- Experience with data cleaning, quality checking, and validation
- Experience applying statistical analysis methods, including regression and correlation, to evaluate strategy behavior and operational risks
- Experience operating in Linux environments, including file operations, process management, text search, and data processing
- Experience designing and building automated tools, alerts, and analytical reporting
- Experience monitoring operational processes and system outputs and escalating anomalies or issues
- Experience preparing technical documentation, research reports, and analytical findings
- Experience collaborating with investment, engineering, and operations stakeholders
- Experience conducting root-cause investigations of operational issues
- Must pass the company's required skills assessment
Two Sigma Compensation & Benefits Highlights
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Strong & Reliable Incentives — Compensation packages for technical roles include substantial performance-based bonuses that create notable upside potential. This structure is described as a key reason total pay feels strong, particularly versus mainstream technology roles.
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Healthcare Strength — Healthcare is described as premium-free for employees and eligible dependents, complemented by life and disability coverage. This comprehensive offering is frequently highlighted alongside positive views of the broader benefits package.
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Parental & Family Support — Support includes financial assistance for family building, paid leave for caregivers, additional bonding time, and backup or discounted in-home childcare in some locations. These programs are presented as a meaningful part of the overall benefits.
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The Company
What We Do
Two Sigma is a leading quantitative investment management and trading firm with more than $80 billion in assets under management. The company applies a scientific approach to investing, combining cutting-edge technology, artificial intelligence, data science, and quantitative research with rigorous human inquiry to capitalize on market opportunities and deliver alpha for investors. Founded in 2001, Two Sigma employs over 1,700 curious minds at its headquarters in New York and in offices around the globe.
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Two Sigma Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Our hybrid work policy requires most employees to be in-office a minimum of five days per month. This combines remote flexibility with twice-monthly in-person collaboration weeks, dedicated to brainstorming, team meetings and building connections.
Typical time on-site:
Flexible
