Senior Quantitative Trader
A technology-driven proprietary trading firm specializing in systematic alpha research and electronic market-making is looking to onboard an experienced Quantitative Trader to join their team. They trade across a multitude of asset classes and trading venues with significant market share and are looking for several Quantitative Traders to join our team across multiple offices. As a Quantitative Trader, you will collaborate with some of the industry's top researchers and developers to design and implement new systematic high-frequency trading (HFT) market-making strategies, leveraging their existing technology and infrastructure. Responsibilities: Design and implement systematic HFT market-making strategies Collaborate with researchers and developers to enhance trading systems Utilize advanced technologies and infrastructure to optimize trading performance Conduct thorough analysis and backtesting of trading strategies Monitor and adjust strategies in real-time to ensure optimal performance Qualifications: Bachelor's, Master's, or PhD in Computer Science, Mathematics, or related fields Deep experience in high-frequency trading Proven track record of at least 2 years with consistently profitable strategies generating high Sharpe Ratios and PnL Proficiency in Python, R, kdb+, or C++ Desire to work in a small, collaborative environment Degree from a top-tier college or university is a plus Passion for new technologies and innovative ideas Strong communication skills
US$150000 - US$200000 per year + Bonus
New York
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Lead Quantitative Researcher - Equity Algo Execution
Job Title: Lead Quantitative Researcher - Equity Algo Execution Location: New York Position Overview: I'm working directly with the Global Head of Equity Capital Markets at a Tier-1 US Investment Bank as the firm is further investing into their agency and principal algo execution business. Due to their continued success in 2024 and recent years, their agency offering has climbed the standings to be one of the Top five (5) across the street. In addition, their PT business has seen an increase in trading volume and revenue which is a direct impact of their QR department. The IB is committed from the top down to scale the team in 2025, adding multiple headcount across QR & Development, but more immediately they looking for an experienced Algo Quant Researcher that is well versed in equities market microstructure and someone to own the end to end process of building novel execution algos. Key Responsibilities: Execution Algorithm Development: Design, develop, and optimize execution trading algorithms (agency and principal) for equities, futures, and options markets, with a strong focus on improving client execution performance. Signals Research & Analysis: Conduct research to identify market signals that can enhance trading strategies and improve execution outcomes for clients. Modeling & Strategy Development: Build and implement advanced quantitative models to guide trading decisions, including single-position and portfolio schedule optimization. Market Microstructure Analysis: Analyze market microstructure in equities and futures markets, understanding order placement methodologies, routing, market impact, and transaction cost analysis. Client-Facing Interaction (CRB Desk Experience): Collaborate with client-facing teams to develop and implement execution strategies tailored to specific client needs. Provide quantitative analysis and strategic insights to enhance client trading performance and achieve optimal execution.
US$325000 - US$450000 per year + salary inclusive of performance bonus
New York
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Quantitative Researcher (VP) - Electronic Execution (Equities)
Job Title: Quantitative Researcher (VP) - Execution Algorithms (Equities) and Electronic Trading Location: New York Department: Equities & Futures Quantitative Research Job Type: Vice President (VP) About: An opportunity within a Tier 1 US Investment bank to join a global team specializing in all aspects of quantitative research for Equities, Futures, and Options execution strategies. The team is responsible for developing and optimizing agency algorithmic strategies, smart order routing (SOR), trading analytics, portfolio construction, risk management, inventory management, and internalization. The group also supports the electronic Futures & Options execution business, combining advanced quantitative techniques with cutting-edge trading technologies to provide innovative solutions and insights. Position Overview: We are seeking a highly skilled and motivated Quantitative Researcher with a strong background in developing execution trading algorithms (both agency and principal). The ideal candidate will possess a deep understanding of trading dynamics, quantitative modeling, and algorithmic strategy development, with expertise in both equity and futures markets. The candidate will also have experience working on a Client-Related Business (CRB) desk, where they will have been responsible for delivering tailored solutions and strategies to clients, optimizing trading execution, and improving overall trading performance. A strong foundation in statistical analysis, machine learning, and optimization techniques will be crucial to success in this role. Key Responsibilities: Execution Algorithm Development: Design, develop, and optimize execution trading algorithms (agency and principal) for equities, futures, and options markets, with a strong focus on improving client execution performance. Signals Research & Analysis: Conduct research to identify market signals that can enhance trading strategies and improve execution outcomes for clients. Modeling & Strategy Development: Build and implement advanced quantitative models to guide trading decisions, including single-position and portfolio schedule optimization. Market Microstructure Analysis: Analyze market microstructure in equities and futures markets, understanding order placement methodologies, routing, market impact, and transaction cost analysis. Client-Facing Interaction (CRB Desk Experience): Collaborate with client-facing teams to develop and implement execution strategies tailored to specific client needs. Provide quantitative analysis and strategic insights to enhance client trading performance and achieve optimal execution. Risk Management: Develop and implement quantitative models to assess and manage trading risk and portfolio risk for both internal and client-facing executions. Back-Testing & Performance Evaluation: Conduct rigorous back-testing and evaluation of execution algorithms and trading strategies to assess their effectiveness and profitability across various market conditions. Machine Learning & Advanced Techniques: Apply machine learning techniques, including classification, reinforcement learning, and dynamic programming, to improve trading strategies and models. Collaboration & Knowledge Sharing: Work closely with other members of the quantitative research team, developers, traders, and risk managers to implement and refine trading strategies and algorithms. Qualifications: Education: Master's or Ph.D. in a quantitative field such as Mathematics, Physics, Computer Science, Financial Engineering, or Statistics. Experience: Proven experience in quantitative research or algorithmic trading, with a focus on execution algorithms (agency or principal). (0r) Previous experience on a CRB (Client-Related Business) desk, delivering execution solutions for clients, is desirable. Technical Skills: Strong proficiency in programming languages such as Python, C++, KDB, or Java. In-depth understanding of quantitative methods, including statistical analysis, time series analysis, regression, and model calibration. Familiarity with optimization techniques, including linear/non-linear programming, stochastic optimization, and dynamic programming. Experience with transaction cost analysis, market impact models, and order routing methodologies. Experience with machine learning techniques, including classification, reinforcement learning, and time-series forecasting, is a plus. Knowledge Areas: Market microstructure and order placement methodologies in equities and futures markets. Risk management models and portfolio construction techniques. Smart order routing (SOR) and transaction cost analysis. Client-Facing Skills: Strong experience in a client-facing role, especially in providing tailored execution strategies and quantitative solutions to optimize client trading outcomes. Soft Skills: Strong problem-solving, analytical, and communication skills. Ability to work in a fast-paced and collaborative team environment. Desirable Attributes: Familiarity with large-scale data sets and high-frequency trading environments. Experience in back-testing algorithms and optimizing execution strategies for different market conditions. Understanding of regulatory environments impacting algorithmic trading and client-facing strategies.
US$325000 - US$425000 per year + salary inclusive of performance bonus
New York
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Execution Trader
An asset manager in NYC is looking for an experienced execution trader to join their quantitative investment team. This role involves managing and enhancing the cross-asset trade execution systems, focusing on futures, options, FX, and LME markets. The trader will aim to minimize market impact and optimize pricing, while also handling on-swap trading and custom baskets. Strong Python skills are essential to improve the automated trading processes and collaborate with the investment team on strategy development. Key Responsibilities: Execute trades across global futures, options, FX, and LME markets, ensuring minimal market impact Understand market microstructure and pricing mechanisms, including settlement and block trading Use FCM execution algorithms and conduct transaction cost analysis (TCA) Manage on-swap trading and custom baskets with counterparties Develop and improve the trade execution platform using Python, including pre-trade simulations and post-trade analytics Familiarity with AWS (Lambda, Airflow) is a plus Requirements: 3-5+ years of experience in trading futures, options, FX, and LME Strong Python skills and experience with Pandas, Numpy, and SQL Ability to take ownership of projects and work in a team-oriented environment Detail-focused, self-motivated, and highly organized
US$200000 - US$350000 per year
New York
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Quantitative Research - ML Equities
A $10bn hedge fund is currently expanding their ML Equities business. More information below. Key Responsibilities: Develop machine learning models to identify market patterns and build trading strategies. Analyze large-scale financial datasets and engineer predictive features. Design, test, and optimize trading algorithms for live execution. Collaborate with portfolio managers, data scientists, and engineers. Stay updated on advancements in AI and quantitative finance. Qualifications: Ph.D./Master's in Computer Science, Mathematics, Statistics, or a related field. Proficiency in Python, R, or C++ with expertise in ML techniques (e.g., neural networks, NLP). Strong problem-solving skills; experience in finance is a plus. Excellent communication and detail-oriented mindset. Why Join Us? Work with a world-class team in an innovative environment. Competitive compensation with performance-driven bonuses. Opportunities for growth and professional development. If interested, please reach out to harry.moore(at)selbyjennings.com.
Negotiable
London
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Quantitative Research / Trading - Entry level
I am working with a highly collaborative, academic fund that is expanding rapidly in London. They are looking for entry level quantitative researchers coming from a PhD. Key Responsibilities: Conduct research to identify and test new trading signals using statistical and machine learning techniques. Develop and refine predictive models to analyze financial markets and uncover opportunities. Collaborate with data scientists and engineers to preprocess and manage large-scale datasets. Design, implement, and backtest quantitative strategies across multiple asset classes. Monitor and improve the performance of existing models and strategies. Preferred Qualifications: PhD in a quantitative field such as Mathematics, Physics, Statistics, Computer Science, Engineering, or related disciplines. Strong programming proficiency in Python, R, or C++. Familiarity with statistical and mathematical modeling techniques. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) is a plus. Ability to tackle complex problems methodically and think critically about data and results. Interest in financial markets or prior exposure to financial data analysis is advantageous but not required. Effective communication skills and a collaborative approach to problem-solving. If there is any interest, please apply directly or reach out to me on harry.moore(at)selbyjennings.com.
Negotiable
London
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Machine Learning Researcher - Dubai
Responsibilities: Lead the development of Machine Learning using to support alpha research. Lead the development of Machine Learning tools to promote trading efficiency. Contribute to the research and trading pipeline, including Risk and Factor Modelling. Requirements: Advanced degree in a quantitative field such as Mathematics, Physics, Computer Science, or Engineering. Demonstrated experience in Machine Learning techniques, including Deep Learning, LLMs, and neural networks (Google DeepMind experience preferred). Strong coding skills in at least one of the following programming languages: Python, R, Matlab and /or C++, C#. 2-4 years' Machine Learning experience. No financial experience required.
Negotiable
Dubai
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C++ Developer
Job Responsibilities: Participate in the development and maintenance of stock and futures products, enhancing the quality of online services through technical solutions, and ensuring the reliability of actual trading. Collaborate closely with researchers to ensure various strategies operate efficiently in real trading environments, generating significant returns. Conduct research and manage programmatic trading desks, including the implementation and deployment of microsecond software desks. Optimize the performance and latency of trading and ordering systems across multiple dimensions, including computing, storage, network, and hardware. Job Requirements: Bachelor's degree or higher in computer science or related fields from reputable universities, with over 2 years of work experience. Proficiency in Linux operating system and one of the following: a. Expertise in C++ and a scripting language b. Expertise in Python 3 and a strongly typed language Familiarity with the production and iteration process of online services, and knowledge of various technical methods to enhance service reliability. Proficiency in best practices such as git, code review, CI/CD, and a strong ability to build tools and strive for excellence. Strong interest in quantitative trading and fluency in Chinese. Bonus Points: Winners of ACM/ICPC, NOI/NOIP, or other informatics competitions. Experience in maintaining large-scale, high-complexity, mission-critical products. Strong system design skills, capable of designing systems with a focus on performance, reliability, and availability. Experience in the underlying development of computer systems such as operating systems, databases, storage systems, or distributed systems.
Negotiable
Singapore
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Options/Vol Quantitative Developer
Location: Miami, FL/New York, New York Summary: A top multi-strategy hedge fund is currently hiring for one of their top systematic volatility PM teams. They are looking to hire a cross-functional quant developer who will work very closely with the portfolio manager and traders. This is a dynamic role where you will wear multiple hats and be a crucial contributor to the team across research, development, and trading. Initial responsibilities will revolve around ad hoc development tasks to support an active, cross-asset vol trading desk. Key Responsibilities: Directly support the PMs and traders Building applications/taking over application library Back-testing and updating pricing models/libraries Strategy implementation Job Requirements: 1+ years of experience Strong coding skills Proficient in Python Ability to communicate and collaborate with PMs, traders, and other teams across the business Preferred Skills: Options or Vol experience Recent experience with front-end development JavaScript/React is a nice to have Previous experience in the financial industry If you or anyone in your network may be interested please apply directly through the link below.
US$150000 - US$200000 per year
Miami
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Quantitative Developer (Options)
We are working with a leading Tier 1 hedge fund that is looking to bring on a Quantitative Developer to continue the build-out of a Cross-Asset Options pod in Miami. In this role, you will work directly with an experienced Portfolio Manager to build and maintain tools and libraries that will support the team's options trading strategies. This is a unique opportunity to contribute to the growth of a high-performance trading team. The position offers flexibility for relocation to Miami or the option to travel to the office on a monthly basis. Responsibilities: Develop and maintain robust applications and tools to support the team's trading strategies and research. Take ownership of the application library and platform, ensuring they are user-friendly, scalable, and efficient for the team's needs. Design and implement backtesting methodologies to evaluate the effectiveness of trading strategies and models. Support the development and ongoing refinement of pricing models and libraries to ensure accuracy and relevance in a dynamic market environment. Build and maintain an organized and accessible model storage and library system, ensuring ease of use and integration with other tools and workflows. Collaborate with Portfolio Managers (PMs) to create ad-hoc tools and solutions tailored to specific needs and requests. Continuously improve existing tools and platforms to enhance functionality, performance, and user experience. Provide technical expertise and support for the implementation and optimization of quantitative strategies. Requirements: 2+ years of experience in a development role on an options trading desk, with a strong understanding of trading workflows and quantitative finance concepts. Expert proficiency in Python for application development and data manipulation. Experience with JavaScript and React is a plus. Demonstrated experience in building, maintaining, and optimizing model libraries to support trading desks, with a focus on usability, efficiency, and integration. Advanced degree (Master's or Ph.D.) in a Quantitative field such as Computer Science, Financial Engineering, Statistics, or a related discipline. Proven experience in implementing systematic derivative strategies, with a solid understanding of pricing and backtesting. Strong problem-solving and analytical skills, with the ability to translate complex quantitative models into user-friendly tools and systems. Experience working in a fast-paced, high-performance environment with a focus on delivering reliable and efficient software solutions. Excellent communication skills, with the ability to collaborate effectively with traders, portfolio managers, and other team members.
US$150000 - US$225000 per year + Discretionary Bonus
Miami
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