Trexquant Investment LP

Manager

• Design, organize, and oversee a series of global quantitative competitions targeting university students and aspiring researchers.
• Collaborate with Trexquant quants and developers to create innovative competition formats that test creativity, quantitative thinking, and problem-solving abilities.
• Develop diverse competition types, including alpha discovery challenges, data-driven forecasting tasks, algorithmic trading simulations, and programming or LLM-based creative problem-solving events.
• Partner with academic institutions and student organizations to promote Trexquant competitions and build a strong university presence globally.
• Manage the competition lifecycle — from concept design, technical implementation, and participant engagement to evaluation and post-event analysis.
• Incorporate feedback and results into Trexquant’s research ecosystem to identify promising candidates and extract new alpha ideas.
• Continuously refine and expand the competition framework to ensure it remains engaging, educational, and effective in identifying top-tier quantitative talent.
• Oversee communication, branding, and content related to competition promotion, ensuring clarity and global consistency.
• Track metrics of participation, performance, and talent conversion, reporting outcomes to the leadership and recruiting teams.

Senior Quant Competition Manager

Data Engineer

• Architect and implement a unified data platform that integrates hundreds of vendor datasets, providing consistent, accessible, and high-quality data to simulators and researchers.**
• Design efficient storage and retrieval systems to support both large-scale historical backtesting and high-frequency research workflows.**
• Develop intuitive researcher interfaces and APIs that allow users to easily discover variables, explore metadata, and assemble data into standardized stocks × values matrices for rapid hypothesis testing.**
• Collaborate closely with quantitative researchers and simulation teams to understand their workflows, ensuring the data platform meets real-world analytical and performance needs.**
• Establish best practices for data modeling, normalization, versioning, and quality control across asset classes and data vendors.**
• Work with infrastructure and DevOps teams to optimize data pipelines, caching, and distributed storage for scalability and reliability.**
• Prototype and deploy internal data applications that enhance research productivity and data transparency.**
• Mentor and guide data engineers to maintain robust, maintainable, and well-documented data systems.**

Senior Data Architect

Backend Engineer

• As a C++ Trading & Simulator Engineer, you will work closely with quantitative researchers and traders to design, develop, and optimize high-performance systems for algorithmic trading. Your responsibilities will include building and maintaining the core infrastructure for trading simulations, data pipelines, and low-latency execution platforms. The ideal candidate will have a strong background in C++ development, and experience in creating scalable, low-latency, high-throughput systems.

C++ Trading Engineer – Simulator

Financial Planning and Analysis

• Manage maintain and advise on fund offering documents, navigate and manage ongoing side letters and agreements for separately managed accounts
• Advise on financial market and global trading regulatory obligations, including filings, cybersecurity requirements, and all manner of nuanced topics in the financial market space
• Support the company's compliance with SEC regulatory requirements and industry best practices by working closely with the company’s Chief Compliance Officer and staff
• Provide guidance to Compliance, Technology, Finance, Investor Relations, and Management teams on financial and business legal risks
• Monitor and interpret changes in securities laws, SEC regulations, and corporate governance trends.
• Manage legal efforts to establish counterparty agreements including global clearing and ISDA agreements.
• Assist with Fund board of director meetings and board governance matters.
• Support other attorneys on a variety of business and technology legal responsibilities.
• Support internal investigations and respond to regulatory inquiries as needed.
• Help develop and maintain internal policies and procedures related to securities law compliance.

Regulatory Counsel, Investment Adviser

Attorney

• Administer and optimize Trexquant’s contract lifecycle by using contract management tools (e.g., Ironclad, Conga).
• Manage legal document execution and storage processes.
• Track contract renewals and compliance obligations.
• Build and maintain Jira or other solution based workflows for legal request intake, approvals, and reporting.
• Proactively identify opportunities to automate and streamline legal and compliance processes.
• Develop workflow descriptions and provide training to improve operational efficiency across the firm.
• Review, negotiate, and redline agreements such as NDAs, vendor contracts, and amendments by using form templates and playbooks.
• Maintain organized filing systems for regulatory and corporate compliance materials.
• Support reporting, audit, and policy implementation efforts.

Legal Operations Manager

Risk

• Oversee and analyze risk factor exposures and trends across company portfolios in global markets
• Develop and manage automated risk models across all traded asset classes, including equities, credit, options, and futures, as well as at the portfolio level
• Design stress-test experiments and present results to senior research team members to broaden our risk considerations across various markets
• Partner with the Strategy, Execution, and Capital Allocation teams to develop and implement enhanced risk policies and ensure optimal risk management
• Collaborate with providers on macro market risk considerations, efficient margin policies, and counterparty exposure
• Present risk metrics and escalations to senior management and the investment committee to support timely decisions on shifting risk dynamics

Senior Risk Manager

Platform Engineer

• Architect and maintain core components of the Data Platform with a strong focus on reliability and scalability.
• Build and maintain tools to manage data feeds, monitor validity, and ensure data timeliness.
• Design and implement event-based data orchestration pipelines.
• Evaluate and integrate data quality and observability tools via POCs and MVPs.
• Stand up a data catalog system to improve data discoverability and lineage tracking.
• Collaborate closely with infrastructure teams to support operational excellence and platform uptime.
• Write and maintain data quality checks to validate real-time and batch data.
• Validate incoming real-time data using custom Python-based validators.
• Ensure low-level data correctness and integrity, especially in high-precision environments.
• Build robust and extensible systems that will be used by data operators to ensure the health of our data ecosystem.
• Own the foundational systems used by analysts and engineers alike to trust and explore our datasets.

Data Platform Engineer

Operations

• Lead the trading team and oversee the firm’s end-to-end trading operations as a systematic trading professional.
• Collaborate closely with operations, execution, and infrastructure teams to ensure trading activities are executed smoothly, accurately, and efficiently.
• Oversee global, multi-asset trading operations—including equities, futures, corporate bonds, and other instruments—to ensure accuracy, efficiency, and reliability.
• Continuously enhance trading workflows and operational scalability with execution, operations, and infrastructure teams.
• Initiate and implement new trading-related projects and manage existing initiatives to optimize performance and minimize friction across systems and processes.
• Provide leadership and mentorship to the trading team, fostering a culture of excellence, accountability, and collaboration.

Head of Trading Operations

Database Administrator

• Install, configure, and maintain database management systems (DBMS) such as MariaDB/MySQL and Postgres.
• Monitor database performance, identify issues, and implement optimizations for efficiency and scalability.
• Perform regular backups, recovery testing, and disaster recovery planning.
• Manage and secure database access and configurations.
• Optimize queries, indexes, and transaction performance.
• Lead schema design and migrations (e.g., Alembic).
• Implement infrastructure-as-code for reliable deployments.
• Collaborate with developers to design, test, and deploy database solutions that support business needs.
• Stay updated on industry trends, best practices, and emerging database technologies.

Full-stack Engineer

• Full lifecycle development of low-latency, high-throughput research and trading systems using C++, C, Java, or Rust.
• Build and optimize data processing pipelines to ensure reliable access to large, high-quality datasets.
• Assist in developing tools for back testing, model training, and strategy evaluation.
• Collaborate with researchers and traders to deliver technical solutions that improve research productivity and trading performance.
• Participate in code reviews, testing, and documentation to maintain high-quality standards.
• Stay abreast of emerging technologies, tools, and best practices, bringing innovative ideas to continuously improve our systems.

Software Engineer - Early Career

• Manage office operations, vendors, and budgets
• Support executives with scheduling, travel, and meetings
• Coordinate team events, setup and breakdown
• Maintain a professional and efficient work environment
• Ensure compliance with workplace and confidentiality standards
• Ensure rooms and common areas are clean and presentable
• Perform routine and preventive maintenance on equipment
• Conduct inventory of supplies and ensure office spaces are stocked with necessary items

Workplace Experience Manager

LLM Engineer

• Design, implement, and fine-tune systems incorporating large language models (LLMs) and other advanced AI techniques for applications such as sentiment analysis, news aggregation, market predictions and data cleaning
• Work with structured and unstructured datasets to train models that generate insights and forecasts for investment strategies
• Continuously enhance performance and efficiency of LLMs to ensure scalability and resource-efficiency
• Partner with portfolio quant researchers to develop models addressing market opportunities and challenges
• Stay abreast of latest NLP and LLM developments and contribute to internal thought leadership
• Deploy machine learning models in production, integrating with existing infrastructure and real-time market data feeds
• Identify risks related to LLMs and implement safeguards for model bias and robustness