Trexquant

The General Counsel will lead strategic legal counsel across corporate, transactional, technology, employment, intellectual property, and cross-border matters for a high-growth financial services company. The role requires a JD, 20+ years of legal experience, and an active bar license.

The Python Engineer will improve and operate trading systems, support integrations with asset classes and prime brokers, and handle monitoring, incidents, and performance optimization. The role requires 3+ years of experience, strong Python and Linux skills, and familiarity with market data and order-entry systems.

The DevOps Engineer builds and scales automation, Kubernetes environments, CI/CD pipelines, and operational tooling for research and trading platforms. The role requires at least two years of Linux-centric DevOps, infrastructure, or SRE experience, with expertise in Kubernetes, pipeline engineering, and observability.

Develop machine-learning models and systematic trading strategies by analyzing large financial datasets, researching quantitative finance techniques, and identifying predictive signals. The role requires a STEM degree, Python fluency, and at least two years of systematic trading experience.

Quantitative Researcher responsible for analyzing execution data, developing market impact and trading cost models, and optimizing execution strategies across equities, futures and other asset classes to minimize transaction costs. Requires 3+ years in electronic execution at a quant trading firm, strong quantitative skills, and Python proficiency.

Senior Data Engineer responsible for building scalable ingestion pipelines, normalizing, and maintaining large-scale financial and alternative datasets from global vendors to support quantitative research and alpha generation. Requires 5+ years data engineering experience in finance/quant environments, strong Python/SQL/Linux skills, and deep knowledge of market/tick/reference data across asset classes.

Early-career Quantitative Researcher developing ML models and trading signals to predict asset movements and build market-neutral portfolios. Requires STEM degree, Python fluency, and passion for machine learning; embedded in Alpha, Data Science, or Strategy teams.

Quantitative Researcher developing cutting-edge ML and statistical models to identify predictive signals in global financial markets. Requires PhD in a STEM field, strong Python skills, and interest in ML/AI; no finance experience needed. Matched to Alpha Research, Data Science, or Strategy Research teams.

Early-career technology transactions attorney drafting and negotiating data licensing and technology procurement agreements for a systematic trading firm. Requires JD, NY bar admission, and 1-3 years of relevant experience.

Build and scale analytics, backtesting, and risk infrastructure for systematic trading across equities, futures, and options. Requires strong C++ skills and options domain expertise.

IT Systems Engineer supporting end-user computing, device management, and IT infrastructure for the India office with light after-hours US support. Requires 2-5 years experience with Windows/macOS, networking, scripting, and endpoint lifecycle management.

Leads design and evolution of core trading, research, and simulation infrastructure, building scalable low-latency systems in Linux with C++/Python. Requires 6+ years experience in high-performance trading systems and collaboration with quant researchers.

Monitors and optimizes trading systems infrastructure, handles incident response, and troubleshoots issues in collaboration with traders and developers. Requires 1+ years experience, Linux/Unix proficiency, Python/Shell scripting, and strong quantitative skills.

Monitors and optimizes trading processes, builds CI/CD pipelines for data/strategy deployment, ensures quality control, and drives operational improvements using Python, Linux, and SQL in a systematic trading environment.

Develops high-performance C++ systems for trading simulations, backtesting, data pipelines, and low-latency execution. Collaborates with quants and traders; requires 2+ years C++ experience with strong algorithms and concurrency knowledge.

Designs and leads unified data architecture integrating vendor datasets for quantitative research, simulation, and alpha generation across asset classes. Requires 7+ years experience in data engineering, Python proficiency, and financial data modeling expertise.

Hands-on Linux Systems Engineer builds and maintains bare-metal servers, manages storage like ZFS, automates with Ansible and Bash, and ensures production reliability. Requires 3+ years Linux experience, physical server management, and on-call rotation with data center travel.

Supports and improves end-user computing, identity, endpoint management, networking, and IT operations for the India office. The role requires 2–5 years of IT support or systems experience, strong Windows and macOS expertise, networking knowledge, and scripting capability.

Build and optimize low-latency, high-throughput C++ and Python infrastructure for quantitative research, trading, simulation, and market-data systems. The role requires at least two years of modern C++ experience, strong Linux systems knowledge, and familiarity with real-time environments.

Develops machine-learning models and systematic trading strategies by analyzing large financial datasets, researching alpha signals, and backtesting hypotheses. Requires a STEM degree, 3+ years in systematic trading, Python proficiency, and strong English communication skills.

Leads a quantitative research function while directly developing and deploying systematic equity and derivatives signals that contribute to live trading P&L. Requires 5+ years of alpha research experience, a STEM degree, strong programming and research-infrastructure fluency, and a proven profitable track record.

Leads and contributes directly to systematic equity alpha research in China, producing scalable signals and influencing live trading P&L. The player-coach role requires a STEM degree, at least five years of relevant experience, strong programming and research infrastructure skills, and a demonstrated record of profitable research.

Develops volatility trading strategies, builds pricing tools, calibrates implied volatility surfaces, and analyzes large datasets for alpha signals in volatility markets. Requires 5+ years in quantitative research focused on volatility, Python proficiency, and STEM degree.

Develops market-neutral trading signals and machine learning models to predict financial asset movements using large datasets. Requires 2+ years in systematic trading, STEM degree, and strong Python skills.

Leads a team developing and implementing systematic ETF trading strategies, including research, backtesting, infrastructure enhancement, and risk controls. Requires 5+ years in quantitative ETF strategies, leadership experience, and proficiency in Python.

Develops, deploys, and optimizes production AI systems using LLMs, NLP, and machine learning tools for quant research and market applications. Requires at least two years of hands-on AI or deep learning experience and familiarity with production model deployment.

Develops quantitative models and trading strategies for futures markets using financial data, machine learning, and statistical analysis. Requires 2+ years experience, STEM degree, and Python proficiency.

Develop machine-learning models and systematic trading strategies from large financial datasets, conducting quantitative-finance research and simulations. The role requires a STEM degree, Python proficiency, strong problem-solving skills, and interest or experience in alpha research.

Manages full-lifecycle recruiting for Research and Engineering teams in quantitative finance and technology, sourcing top talent in data science, ML, and software engineering. Requires 3+ years experience in technical hiring and bachelor's degree.

Leads a team to develop, implement, and trade systematic macro strategies across asset classes like FX, integrating into quantitative trading processes. Requires 5+ years in macro strategy research/trading, team leadership, strong quant skills, and Python proficiency.

Develop machine-learning and statistical trading signals for liquid financial assets, analyzing large datasets and testing quantitative-finance hypotheses through simulations. The role requires a STEM degree, Python proficiency, strong problem-solving skills, and an interest in machine learning.