Quantitative Research & Trading

Quantitative Risk Analyst

Role: Quantitative Risk Analyst Location: Amsterdam, Netherlands Blend quantitative analysis with risk management and develop models and algorithms to enhance trading strategies and support risk management at a fast-growing energy trading firm. Responsibilities Model Development: Create models for risk assessment and trading optimization. Data Analysis: Analyze data to inform strategies. Proactive Ideation: Generate insights to improve profitability. ETRM Implementation: Integrate and customize the ETRM system. Risk Monitoring: Identify and monitor trading risks. Reporting: Prepare PnL and position reports. Risk Modeling: Develop advanced risk models. Policy Implementation: Ensure compliance with risk policies. Market Modeling: Predict price movements and trends. Derivative Pricing: Price complex energy derivatives. Volatility Hedging: Develop volatility models and hedging strategies. Algorithmic Trading: Design trading models and strategies. Load Forecasting: Forecast electricity demand. Machine Learning: Implement ML models for trading. Backtesting: Validate models before deployment. Trader Support: Provide real-time analysis and tools. Data Infrastructure: Develop data pipelines for trading systems. Requirements Experience: 3-5 years in, preferably in gas and power trading. Education: Master's in Computer Science, Mathematics, Quantitative Finance, or related field. Technical Skills: Advanced Python, familiarity with C++ and SQL, strong quantitative skills. Analytical Skills: Data analysis and risk management experience. Teamwork: Effective collaboration skills

Amsterdam

Senior Quantitative Researcher Opportunity - London/Paris/Dubai

**Location: London, Paris, Dubai** A leading hedge fund with over £5 billion in AUM is seeking a senior quantitative researcher to head its mid-frequency equity trading initiatives. This role comes with high responsibility, as the successful candidate will drive strategy development, oversee portfolio execution, and manage significant portions of the equity book. Reporting directly to senior leadership and collaborating closely with the PM, this position provides a unique opportunity to shape the fund's mid-frequency equity strategy and deliver impactful results. Key Responsibilities: - Lead the development and refinement of mid-frequency trading models to generate alpha in equity markets. - Conduct research to identify and validate new trading signals and opportunities through statistical analysis, large datasets, and machine learning. - Perform extensive backtesting and forward testing to ensure model robustness and adaptability in different market conditions. - Collaborate with the PM and senior team members to implement and execute trading strategies effectively. - Continuously monitor, assess, and adjust strategies to optimize performance and manage risk. Requirements: - Advanced degree (Master's or Ph.D.) in a quantitative field (Mathematics, Computer Science, Engineering, etc.). - Proven experience leading mid-frequency trading strategies within equity markets. - High proficiency in programming (Python, R, or similar), with a focus on algorithmic development and data analysis. - Strong expertise in statistical modelling, machine learning, and managing large datasets. - Deep knowledge of market microstructure, risk management, and performance attribution relevant to mid-frequency trading.

US$300000 - US$600000 per year

Quantitative Researcher - US Equities | NYC

Quantitative Researcher - US Equities | NYC A top systematic trading pod is looking to add an experienced quant researcher to the team. This team leverages alternative and fundamental data to develop systematic strategies within the US Equities space. This is an excellent opportunity for an experienced individual to take the next step in their career and work amongst a highly successful team that provides amazing flexibility in terms of day-to-day research projects, and longer-term career aspirations. Responsibilities: Work with the lead PM on full end-to-end strategy research including idea generation, model development, portfolio construction/optimization, backtesting and implementation. Leverage statistical research and fundamental financial insights to build predictive models and identify investment opportunities. Use statistical models to analyze alternative data sets and data sources to identify investment opportunities within the US or global equity markets. Collaborate with the senior PM and other researchers on end-to-end strategy research in a collaborative environment. Required Skills: 2+ years of experience in systematic equities alpha research, with a preference for mid/high frequency (intraday to daily) from a competing buyside trading team. This is an active search for the team and they would highly prefer candidate with a non-compete less than 9 months. Experience with equity portfolio construction, optimization, and equity risk modeling. Advanced degree (MS/PhD) in a quantitative discipline preferred but not required. Experience leveraging alternative or fundamental data sets, and strong understanding of traditional economic topics. If there is an interest, please click the APPLY NOW button below.

US$200000 - US$600000 per year

Equity Execution Quant Researcher

Equities Execution QR @ $10bn AUM Quant Fund Currently working with the Head of Global Execution at a top hedge fund in NY. The team is looking to bring on an equity execution quant researcher to the team ideally coming from an investment bank. This is a very exciting opportunity as the team provides execution services to the entire firm and you will be responsible for speaking with brokers, developing execution algos and working very closely with veteran PMs. Requirements -5+ years of sell side experience in equities on an execution desk -Experience working on execution, algo research, TCA etc is mandatory -Expert Python and KDB programming -Strong communication skills If you are looking to be a part of a growing team within a highly regarded hedge fund, then please apply here!

US$300000 - US$550000 per year

Structured Credit Quant

Summary: A top credit fund with $10 billion in AUM has a new initiative to expand their NYC team. Specifically the fund is diversifying their strategies and has multiple headcount for quants at the Associate to senior Vice President level. In this role you will work with a larger group to support the businesses PM's through developing a scalable framework that houses new tools and analytics. They are looking for someone with strong background in structure credit products and have proficient python skills. They are looking for someone to bring new ideas to the table, while also contributing to the collaborative nature of the team. Job responsibilities include: Work to support Traders/Portfolio Managers to build quantitative models, tools, analytics, dashboards for identifying new opportunities Develop desktop applications using data science and machine learning techniques Analyze large data sets to create and implement new strategies Job requirements include: A Master's or Ph.D. degree in a quantitative field such as Mathematics, Statistics, Computer Science, Physics, Engineering, or Financial Engineering. 3-10 years of Front Office experience supporting a credit and/or mortgage trading desk Proficient in Python, C++, or another object oriented programming language Strong communication and collaboration skills across various teams within the organization

HF Quantitative Researcher Opportunity in Amsterdam/London

**Quantitative Researcher in High Frequency wanted** Location: London, Amsterdam A Prop trading firm is looking for a skilled quant researcher to join their high-frequency equity trading team. The role offers fast progression, with successful candidates having the opportunity to step into a sub-PM position, taking ownership of a portion of the trading book. You will work closely with the PM in a highly experienced team, contributing directly to the firm's performance in a dynamic, fast-paced environment. Key Responsibilities: Develop and implement high-frequency trading models for equity markets. Research new trading signals using large datasets, statistical techniques, and machine learning. Conduct backtesting and real-time testing to ensure the robustness of models. Work with the PM to refine and execute trading strategies. Monitor strategy performance and adjust as needed to optimize results. Requirements: Master's or Ph.D. in a quantitative field (Mathematics, Computer Science, Engineering, etc.). Experience developing high-frequency trading strategies in equity markets. Proficiency in C++, Strong background in statistical modelling, signal generation, and working with large datasets. Knowledge of market microstructure and high-frequency execution.

Amsterdam

Quantitative Researcher - Equities and Futures

Systematic Equities Quantitative Researcher Opportunity in London We are working with a top global hedge fund that is looking for high-quality talent. Our client is looking for a Quantitative Researcher specialising in Machine Learning to join their Systematic Equities Team in London. As part of the team, you will focus on: Collaborating directly with the Portfolio Managers to develop systematic trading strategies Modelling implementation and back testing Data analysis and research for global equity strategies Required Skills: Expert in Python. Demonstrated knowledge of quantitative finance, mathematical modelling, regression. 2+ years' experience working in systematic trading with a focus on equities. Advanced degree in Machine Learning, Mathematical Finance, Statistics, Financial Engineering or other related degree.

City of London

Commodity Quant Analyst

Introduction: Our client, a Tier 1 Investment Bank are seeking a Commodity Quant Analyst to support their commodity trading business. You will come in as the lead quant support in London. As part of this role you will responsible for the innovative modelling of commodity products and payoffs. You will also work very closely with trading, providing ad-hoc tool building and help systematise their trading strategies. The bank's culture is very collaborative and there is emphasis placed on a good work-life balance. Key Responsibilities: Develop and implement quantitative models for pricing, risk management, and trading strategies in the commodities markets. Conduct research and development of new analytical frameworks and financial models tailored to commodities. Build and maintain end-user tools in Python, providing user-friendly interfaces for in-house analytics models and machine learning tools. Collaborate closely with traders, risk managers, and other stakeholders to address quantitative modeling issues and support trading activities. Engage with outside organizations to help them comprehend and use front-office analytics models. Required Skills and Qualifications: An advanced university degree in a STEM subject A minimum of 3 years of industry experience in front office positions is required Previous experience with metals products and models is highly desirable. Proficiency in software development using Python, C#, C++, and/or .NET. Strong communication and interpersonal skills, with the ability to interact effectively with a wide range of stakeholders How to Apply: Interested candidates are invited to submit their resume with their relevant experience and qualifications

ML Research Scientist

A leading hedge fund are currently looking for senior Machine Learning Research Scientists to join their team. Information below. Responsibilities Research and develop machine learning models for financial market predictions. Build and optimize algorithms for trading strategies across various asset classes. Perform data analysis, feature engineering, and model backtesting. Collaborate with engineers and traders to deploy models. Stay current on AI/ML advancements to improve trading strategies. Requirements Ph.D. or Master's in Computer Science, Machine Learning, Math, Physics, or related fields. 3+ years of ML experience; financial background preferred but not required. Proficiency in Python, ML frameworks (e.g., TensorFlow, PyTorch), and time series analysis. Strong problem-solving skills and ability to work in a fast-paced environment What They Offer Competitive salary, bonus, and equity participation. Growth opportunities and access to top-tier resources. Flexible work arrangements, excellent benefits, and wellness programs. If interested, please apply directly or reach out to harry.moore(at)selbyjennings.com.

HFT Futures Quant Trader

A high frequency trading firm based in London is looking for a HFT futures trader with 1-5 years of experience. The firm have a world class technology and infrastructure setup, and have a collaborative environment within the team. The team is headed by an individual who has had 9 years of experience across multiple tier-1 proprietary trading firms. The compensation provided is market competitive and for the right candidate, formulaic. Responsibilities: Develop and implement high-frequency trading strategies for futures markets, utilising advanced quantitative techniques, statistical models, and machine learning algorithms. Collaborate closely with our technology team to design and optimise proprietary trading systems and algorithms for speed, efficiency, and reliability. Conduct extensive research and data analysis to identify market patterns, trading signals, and pricing inefficiencies for alpha generation. Monitor and manage trading positions in real-time, ensuring optimal execution and risk management in rapidly changing market conditions. Participate in the development and enhancement of trading infrastructure, data feeds, and connectivity to exchanges and trading platforms. Requirements: Master's or Ph.D. degree in a quantitative field such as Finance, Mathematics, Computer Science, Statistics, or related disciplines. Proven experience as a High-Frequency Futures Quantitative Trader, with a strong track record of success in designing and executing trading strategies in fast-paced markets. Proficiency in programming languages such as Python, C++, or Java for data analysis, model development, and building automated trading systems. Sound understanding of futures markets, market micro-structure, and trading technologies. Experience with low-latency trading systems, direct market access, and trading infrastructure optimisation is highly desirable.

Quantitative Researcher - Interest Rates

An industry-leading global macro hedge fund is seeking a talented Quantitative Researcher to join their Rates Investment team. This role involves developing innovative trading tools and analytics that drive profitability. The ideal candidate will have strong mathematical, programming, and analytical skills, with a proven track record in building reliable quantitative models. Key Responsibilities Design and implement advanced quantitative models for the Rates desk, working closely with the business to understand key objectives. Build and maintain risk management tools, pricing models, yield curves, and analytics for real-time decision-making. Identify and exploit relative value opportunities in the Rates market. Collaborate with other quants, developers, and traders to support the ongoing enhancement of tools. Support and troubleshoot key pricing and risk systems used across the firm. Key Qualifications Strong academic background with a first-class degree and/or advanced degree (MA/PhD) in a quantitative field from a top-tier university (QS Global top 200). 2+ years of experience in financial services, with a focus on the Rates market. Expertise in data analysis using Python and object-oriented programming (C++, C#, or Java). Proven experience in developing and optimising pricing and risk models. Excellent understanding of derivatives, particularly in the context of interest rates. A pragmatic problem-solver with the ability to work independently as well as in a team setting.