Key Skills & Requirements:

• Core Technical
• Strong Python proficiency — you'll refactor research code into robust, tested production pipelines daily
• Awareness of performance and optimisation — profiling, memory management, and computational efficiency when scaling research code across large universes
• Solid software engineering practices: version control, unit testing, code review, CI/CD, and refactoring — you care about code quality, not just code that works
• Comfortable on Linux platforms with working knowledge of shell scripting
• Experience with data analysis libraries (NumPy, SciPy, pandas) and handling large datasets
• Familiarity with databases and data infrastructure (SQL, data pipelines, or tools like ArcticDB)
• Exposure to ML/DL frameworks (PyTorch, TensorFlow, scikit-learn) or LLM-related tooling
• Research & Domain
• Relevant mathematical knowledge — statistics, optimisation, or factor modeling — enough to understand the research you're productionising
• A keen interest in financial markets and how quantitative strategies are built and deployed
• Nice-to-Haves
• Prior internship in quantitative development, systematic investing, or front-office technology
• Education
• Currently enrolled at a top-tier university in Computer Science, Software Engineering, Mathematics, Physics, or a related field with strong computational content

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

We're looking for an experienced, detail-oriented Risk Associate to join our global team. This unique position is ideal for candidates with strong risk management skills, technical proficiency, and a readiness to contribute to the operational flow of global trading. You will be immersed in both risk management and post-trade operations, gaining broad exposure and playing a key part in the reliability and safety of our trading activity. 

This is a 4-day workweek role, with one weekend day (Saturday or Sunday) as part of your schedule. During onboarding and training, you’ll initially work a standard Monday–Friday week before transitioning to the 4-day schedule (Wednesday–Saturday or Sunday–Wednesday). Candidates must be comfortable with and prepared for this arrangement. Flexibility and reliability to support weekend trading are essential to success in this role. 

What You’ll Do: 

• Participate in daily and real-time risk monitoring across asset classes, helping to identify, assess, and address risk exposures related to trading activities 
• Use and develop your Python, SQL, and Excel skills to analyze large datasets, automate reporting, and support projects related to market risk (such as VaR, factor models, and portfolio analytics) 
• Work closely with trading, technology, treasury, clearing, and compliance teams around the globe. 
• Support daily clearing activities including trade reconciliation, resolving breaks, and ensuring smooth post-trade workflows across various products and venues 
• Suggest enhancements to workflows and documentation, actively build your expertise, and contribute to team projects focused on continuous improvement 
• Other duties as assigned or needed  

Skills You’ll Need: 

• 5+ years of relevant risk management, trading, or financial operations experience, ideally at a trading firm, hedge fund, asset manager, or investment bank 
• Hands-on familiarity with at least one major asset class (Equities, Treasuries, Futures, FX, or Options); willingness to expand your multi-asset risk expertise 
• Strong proficiency in Excel (using pivot tables, v-lookups, etc.); experience with Python (including libraries such as Pandas, NumPy, SciPy) and SQL is highly valued 
• Comfort with analyzing financial data (daily or intraday) and building tools for automation or reporting 
• Effective communicator, able to explain technical and financial concepts clearly to a variety of audiences 
• Self-motivated, proactive, and able to learn quickly on the job 
• Bachelor’s degree in a quantitative, technical, or business field 
• Reliable and predictable availability 

Bonus Points: 

• Experience with post-trade clearing systems or break resolution 
• Familiarity with risk modeling or analytics (such as VaR, factor models, or portfolio analysis) 
• Experience with Linux/Unix environments or in 24/7 trading operations 

About Us

AXQ Capital is a global quantitative investment firm with offices in New York, Beijing, Shanghai, and Hong Kong. We pursue consistent alpha through rigorous scientific research and sustained investment in technology and data infrastructure. Our strategies are deployed across global markets, spanning multiple geographies, asset classes, and trading horizons.

Job Duties 

As a Machine Learning Researcher, you will develop ML/DL models to generate alpha from large-scale financial and alternative datasets. Working closely with portfolio managers and senior quantitative researchers, you will conduct research across a range of trading strategies within a fast, iterative research-feedback loop.

Qualifications

Below is a list of skills and experiences we believe are relevant. Even if you don’t consider yourself a perfect match, we still encourage you to apply because we are committed to helping our people grow and develop.

• Master’s or PhD from a top-tier university in a quantitative discipline (e.g., mathematics, physics, statistics, computer science, or related fields)
• Strong foundation in machine learning, statistics, and optimization, with deep expertise in at least one area such as time series modeling, NLP, or LLMs
• Strong communication skills and ability to collaborate effectively in a research-driven environment
• Experience with the Python scientific and ML ecosystem (e.g., NumPy, Pandas/Polars, PyTorch, TensorFlow)
• Proven ability to build and improve models that perform under noisy, non-stationary, and high-dimensional data conditions
• Intellectually curious, highly analytical, and driven to discover alpha in complex systems
• Self-motivated and highly productive, with strong ownership and a bias toward action
• Publications at top-tier venues such as NeurIPS, ICML, KDD, or IJCAI
• Strong track record in competitive ML platforms (e.g., Kaggle) or academic competitions
• Prior experience in quantitative research, systematic trading, or alpha signal generation

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Jump Trading's Post Trade Analytics Team plays a crucial role in measuring and optimizing performance and trade execution across all global markets where the firm operates. This team is responsible for developing, operating, and maintaining performance measurement solutions, as well as conducting a wide range of post-trade analyses for various departments, including trading, business development, and other central teams. Daily, the team's core infrastructure collects, organizes, and stores billions of data points related to trading performance.

This role offers the opportunity to develop both business and technical expertise while significantly contributing to our global post trade analytics effort. We are seeking an experienced Data Engineer with 3+ years of experience to work closely with our Shanghai team, building and maintaining sophisticated datasets and data pipelines that will shape the way we trade.

What you’ll do:

• Build, operate, and maintain complex datasets and end-to-end dataset pipelines for analytics and research use cases.
• Partner directly with traders, quantitative researchers and data scientists to understand data requirements and deliver reliable data products in both real-time and next-day environments.
• Ensure data quality and reliability through validation frameworks, monitoring, alerting, lineage, and incident response.
• Optimize data processing and workflows for performance, cost, and robustness; troubleshoot pipeline failures and production issues.
• Maintain and improve associated internal tools, documentation, and operational runbooks.

Skills you’ll need:

• At least 3+ years’ experience as a Data Engineer
• Proficient in Python development, DevOps, and Linux environments.
• Proven expertise building and operating ETL/ELT pipelines (including orchestration, scheduling, and dependency management).
• Hands-on experience with relational and non-relational databases, including schema design and query optimization.
• Familiarity with SQL and data analytics tools and libraries, such as Pandas and NumPy.
• C++ experience is a plus.
• Strong analytical and problem-solving abilities.
• Other Duties as assigned and needed.
• Reliable and predictable availability.
• Shanghai based