• Research time-series methods, advanced statistical techniques, and machine learning models to extract predictive value from complex datasets.
• Analyze large, noisy, real-world data sets to identify systematic trading opportunities.
• Help develop statistical and ML-based tools and techniques to solve complex data-related problems throughout the research process.

• Your primary focus throughout the day will be on researching new statistical techniques, exploring datasets, and prototyping signal variants.
• Apply critical thinking at every step—rigorously backtesting ideas, diagnosing overfitting, and questioning your own assumptions.
• Discuss and present research results with your immediate team, portfolio managers, and senior management, actively incorporating their feedback.
• Document your work cleanly and clearly so colleagues can easily build upon your findings.

• Quantitative Background: Pursuing a Bachelor's, Master's, or PhD in computer science, statistics, machine learning, signal processing, optimization, mathematics, physics, or a related STEM subject.
• Research Excellence: Demonstrated ability to conduct high-quality, in-depth, and rigorous research on real-world data, along with the ability to communicate complex results clearly to both technical peers and senior stakeholders.
• Programming Proficiency: Strong proficiency in Python, with a solid understanding of data structures, algorithmic complexity, and numerical libraries (e.g., pandas, numpy).
• Statistical & ML Knowledge: Strong grasp of probability, statistics, linear algebra, time-series analysis, and machine learning, including the practical ability to recognize and mitigate overfitting.
• Team Player: Strong communication skills with the ability to work well in a collaborative, high-pace setting, driving projects to completion across accelerated timelines and coordinating with colleagues across multiple regions.

• Prior internship in quantitative research or systematic investing.
• Hands-on experience working with noisy, large-scale financial or alternative datasets.

How to Apply
Apply online with your CV and a short cover note. In your cover note, describe one real research or engineering problem you worked on: what you tried, what worked, what didn't, and what you would do differently.

ABOUT US

Capco is a global technology and management consultancy specializing in driving digital transformation in the financial services and insurance industries. Capco is committed to providing clients with practical solutions. We offer a globally integrated service with offices in leading financial centers across the globe. We have the people, the vision, and the passion.

We are growing through a significant growth journey, now is a very good time to join us as we expand geographically, increase headcount and disrupt the consulting market across APAC with entrepreneurial and agile thinking.

We are:

• Experts in banking and payments, capital markets and wealth and asset management
• Deep knowledge in financial services offering, including e.g. Finance, Risk and Compliance, Financial Crime, Core Banking etc.
• Committed to growing our business and hiring the best talent to help us get there
• Focus on maintaining our nimble, agile and entrepreneurial culture

ROLE RESPONSIBILITIES

We are currently seeking Senior Data Consultants to support and drive the growth of our Data practice, particularly in our Python Development stream. This is an exciting opportunity to be a leader, in a growing team of data practitioners, where you will be initiating and implementing cutting-edge data & analytics programmes for top-tier Financial Services clients.

As a Senior Data Consultant, you will be involved in developing the HK Data Practice capabilities and the broader Global Data Practice to supporting topics such as Cloud, Artificial Intelligence and Machine Learning.

KEY RESPONSIBILITIES 

SKILLS & EXPERTISE

• 5 years of experience in python development within Financial Services. 
• Advanced proficiency in Python for data processing and analytics, including libraries such as pandas, NumPy, and related frameworks.
• Strong understanding of data warehousing concepts, data modelling principles, and data governance standards.
• Solid experience working within SDLC and Agile delivery environments as a strong individual contributor.
• Experience with FIS tools, including Prophet and PMCS (configuration, runs, outputs, integration
• CI/CD: automate tests/quality checks in pipelines (e.g., GitHub Actions/GitLab/Jenkins)
• Immediately available highly preferred 

WHY JOIN CAPCO?

You will work on engaging projects with some of the largest banks in the world, on projects that will transform the financial services industry.

Job Description

We are seeking a Portfolio Manager (PM) to lead our top-level capital allocation for our crypto portfolio. You will not just manage a book; you will design and execute the "Ensemble Strategy" that dictates how capital flows between strategies and emerging venues. Your mission is to engineer a "Weather-Proof" portfolio that extracts idiosyncratic alpha from disparate markets while maintaining a strictly controlled risk profile.

Responsibilities

• Dynamic Asset Allocation: Oversee the deployment of capital across the multi-strategies
• Ensemble Optimisation: Build and maintain quantitative frameworks (Risk Parity, Mean-Variance, or Bayesian models) to determine optimal weights based on real-time volatility and correlation.
• Regime-Based Hedging: Utilize Prediction Markets and FX to hedge tail risks and macro shifts impacting the core Crypto portfolios.
• Risk Budgeting: Define and monitor VaR, Stress Tests, and Drawdown limits for individual strategy sleeves.
• Cross-Asset Research: Identify "Lead-Lag" relationships—e.g., how movement in the US Dollar (DXY) or Treasury yields impacts Crypto liquidity and Commodity pricing.

Requirements

• Experience: 5-10 years in a Senior Quantitative Allocation role at a fully systematic multi-strat hedge fund, prop shop, or family office.
• Multi-Asset Mastery: Proven track record managing risk across different systematic strategies. Experience in Prediction Markets (Polymarket, Kalshi) or Event-Driven Trading is a significant plus.
• The Stack: Expert proficiency in Python (NumPy, Pandas, PyTorch/TensorFlow) and SQL/KDB+.
• Quantitative Depth: Mastery of portfolio construction mathematics, including covariance matrix estimation and L^2 regularization.
• Education: Advanced degree (Masters/PhD) in Mathematics, Physics, Computer Science, or Financial Engineering.

Who You Are

• The Aggregator: You don't just look for "good trades"; you look for how trades fit together to improve the fund's overall Information Ratio.
• The Risk-First Thinker: You understand that in a levered multi-asset environment, correlation is the silent killer.
• The Adaptable Architect: You are comfortable transitioning from the 24/7 volatility of Crypto to the structural nuances of the Commodities curve and the binary outcomes of Prediction Markets.

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors. 

We are looking for an exceptional Data Scientist to join the Data Search & Analytics team. In this role, you will work between the Research and Trading desks, and the Engineering team to ensure the successful leveraging of data at the firm.

Your future role within QRT

This team is integral to the firm’s success. As such, your responsibilities will include:

• Collaborating with Quantitative Researchers and Traders to design datasets that drive systematic strategies and to inform discretionary trading decisions
• Prototyping and designing code to extract, clean, and aggregate data from a wide range of raw sources and formats
• Working with Engineers to automate and optimise your code, ensuring robust data extraction processes
• Managing the end-to-end process of onboarding new datasets
• Proactively solving data related problems to minimise time to production
• Innovating and experimenting with novel data extraction methods to enhance the firm’s data onboarding toolkit

Your present skillset

• 3+ years of experience as a Data Scientist (or similar position); experience in a buy-side quantitative finance role is advantageous
• Postgraduate degree in a quantitative discipline such as Mathematics, Physics or Engineering.
• Advanced programming experience in Python, including proficiency with data handling libraries such as Pandas and NumPy
• Demonstratable interest in financial markets and the application of data in its analysis and understanding
• Experience working with both traditional and alternative financial datasets
• Excellent communication skills, with the ability to effectively collaborate with all stakeholders, including researchers, traders, engineers, management, and external vendors
• Ability to work in a high-performance, high-velocity environment

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped our collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

Your future role within QRT

• Design, develop, and maintain software solutions with clean, modern architecture
• Partner with front office to drive technical solutions around new trading initiatives
• Communicate with quants and traders regularly to deliver bespoke solutions
• Bring in new ideas and insights using data driven pipelines and analytics

Your present skillset

• 2-8 years of software development experience
• Solid experience in Python and core libraries such as Numpy, Pandas is a must
• Proven understanding of modern software architecture
• Strong computer science fundamentals
• Experience with Linux environments, Cloud Platforms (AWS preferred) and Containerized applications (Docker preferred)
• Experience with other programming languages such as Java, C++, C# is a plus, but not necessary
• Agility to work in a fast-paced environment with varying demands
• Strong team-player
• Strong communication skills essential
• Previous experience in finance is an advantage, but not a must

ABOUT CUBIST 

Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

ROLE

The candidate will be responsible for some or all of parts of the research pipeline—including data processing, feature design, model training, portfolio construction and management, back-testing, and performance analysis. Successful researchers combine statistical analysis, machine learning techniques, intense passion, and curiosity to decipher the market, and aspire to gain great intellectual understanding and financial outperformance.

RESPONSIBILITIES

• Finding alphas in global equity markets by applying rigorous statistical analysis on technical data or alternative data sets. Performing hypotheses testing, feature design, and backtesting to improve on alpha ideas.
• Maintaining and improving the research pipeline, including alpha generation, portfolio construction, back-testing, and monetization.
• Maintaining and improving portfolio trading in production environments.

REQUIREMENTS

• Bachelors degree or higher in mathematics, statistics, computer science, or other quantitative discipline.
• 2+ years of experience in quantitative research. Experience in medium frequency equity research is a plus.
• Strong analytical and quantitative skills; solid knowledge in statistics, linear algebra, or machine learning.
• Proficiency in Python. Familiarity with scientific toolkits, such as Numpy and Pandas.
• Ability to work both independently and collaboratively within a team.
• Commitment to the highest ethical standards.

Flow Traders is looking for a Senior Research Engineer to join our Hong Kong office. This is a unique opportunity to join a leading proprietary trading firm with an entrepreneurial and innovative culture at the heart of its business. We value quick-witted, creative minds and challenge them to make full use of their capacities. 

As a Senior Research Engineer, you will be responsible for helping to lead the development of our trading model research framework and using it to conduct research to develop models for trading in production. You'll expand the framework to become global standard way of training, consuming, combining, and transforming any data source in a data-driven systematic way. You will then partner with Quantitative Researchers to build the trading models themselves.

What You Will Do

• Help to lead the development and global rollout of our research framework for defining and training models through various optimization procedures (supervised learning, backtesting etc.), as well as its integration with our platform for deploying and running those models in production
• Partner with Quantitative Researchers to conduct research: test hypotheses and tune/develop data-driven systematic trading strategies and alpha signals

What You Need to Succeed

• Advanced degree (Master's or PhD) in Machine Learning, Statistics, Physics, Computer Science or similar
• 8+ years of hands-on experience MLOps, Research Engineering, or ML Research
• A strong background in mathematics and statistics
• Strong proficiency in programming languages such as Python, with experience in libraries like numpy, pytorch, polars, pandas, and ray.
• Demonstrated experience in designing and implementing end-to-end machine learning pipelines, including data preprocessing, model training, deployment, and monitoring
• Understanding of and experience with modern software development practices and tools (e.g. Agile, version control, automated testing, CI/CD, observability)
• Understanding of cloud platforms (e. g., AWS, Azure, GCP) and containerization technologies (e. g., Docker, Kubernetes)

Flow Traders does not accept unsolicited resumes from any professional staffing or search firms. All resumes, and any other information identifying potential candidates, submitted to any employee at Flow Traders via-email, the Internet or directly without a valid and signed search agreement will be deemed free to contact by Flow Traders without any restrictions and no placement fee of any kind will be paid in the event the candidate is hired by Flow Traders.

Flow Traders is looking for an experienced Quant Trader to join our Equity Delta One desk in Hong Kong. You'll design and execute mid-frequency (minutes to hours) and relative value strategies across exchange-traded equity products in Asia, directly impacting desk P&L. This is a market-facing role with opportunities to expand into cross-asset strategies and collaborate with technology teams on cutting-edge trading infrastructure.

What You Will Do 

• Trade and manage positions in single stocks, single-stock futures, index futures, and ETFs.
• Develop, deploy, and refine systematic trading strategies, with a focus on mid-frequency horizons.
• Conduct quantitative research, probability and statistical analysis to identify opportunities.
• Translate trading intuition into structured, production-ready strategy deployment plans.
• Optimize execution algorithms and partner with technology teams to optimize trading and research infrastructure
• Perform post-trade analytics to improve models and execution quality.

What You Need to Succeed

• Bachelor's/Master's in Finance, Mathematics, Engineering, Computer Science, Physics, or related.
• Experienced in systematic trading strategies, with slight preference for mid-frequency strategies (holding times from minutes to hours).
• Strong knowledge of probability and statistics.
• Experience in deployment and productionization of trading strategies.
• Ability to translate trading intuition into structured strategy deployment plans.
• Strong programming skills in Python or C++ (NumPy, pandas, statistical packages).
• Strong work ethic and ability to perform under pressure.
• Analytical, detail-oriented, and comfortable in fast-paced, systematic environments.

Nice-to-Have Skills:

• Experience with market microstructure, transaction cost analysis, and execution optimization.
• Familiarity with portfolio construction and risk models.

Flow Traders does not accept unsolicited resumes from any professional staffing or search firms. All resumes, and any other information identifying potential candidates, submitted to any employee at Flow Traders via-email, the Internet or directly without a valid and signed search agreement will be deemed free to contact by Flow Traders without any restrictions and no placement fee of any kind will be paid in the event the candidate is hired by Flow Traders.

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.

Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.

*Candidates for this off cycle internship should be graduating in 2026 or 2027 and be interested in working in Hong Kong for their full-time job after graduation. 

• Building and improving high-performance data pipelines and processing systems
• Collaborating with quantitative researchers to develop tools that support research workflows
• Optimizing system performance through profiling, debugging, and architectural improvements
• Building shared tools and infrastructure that power research efficiency and shorten iteration cycles
• Bridging the gap between research prototypes and production-grade systems

• Solid foundation in C++ and Python programming
• Solid understanding of computer science fundamentals: data structures, algorithms, memory management, operating systems, compilers, computer architecture, and networking
• Interest in systems programming and understanding how software interacts with hardware (OS internals, process scheduling, I/O, caching)
• Comfortable working in a Linux environment
• Passion for writing clean, efficient, and maintainable code; comfortable contributing to collaborative codebases
• Ability to translate research requirements into robust software solutions
• Strong learning ability and intellectual curiosity
• Good communication skills with users and other stakeholders
• Reliable and predictable availability
• No finance or economics study or work experience required
• Other duties as assigned or needed

• Curiosity for data-driven approaches and ability to work with large-scale data from first principles, not just relying on libraries
• Experience with performance optimization or low-latency systems
• Familiarity with HPC or distributed computing
• Exposure to data analysis tools (Pandas, NumPy) or statistical methods
• Past internship or job experience in a software development role