Quant Deveveloper - Data
Your Future Role Develop ETL pipelines to integrate and test large alternative datasets for the Commodities desk, collaborating with quant researchers and data engineering teams. Architect, deploy, and manage cloud-based systems for storing and exploring large alternative datasets with the AWS infrastructure team. Monitor, support, debug, and extend existing Commodities trading and research infrastructure alongside Researchers and Support Engineers. Your Present Skillset Proficient in Python, especially numerical libraries (numpy, pandas, matplotlib, etc.) Basic knowledge of AWS and databases (e.g., SQL) Familiar with development practices such as version control (Git) and unit testing Quantitative mindset Team player with a collaborative attitude Nice to Have Experience creating dashboards or using data visualization software (e.g., Tableau, Dash) Advanced AWS experience (e.g., DynamoDB, RDS, S3, Lambda, AWS CDK) Advanced database knowledge (query optimization, relational vs. non-relational databases, etc.) Parallel computation experience Experience with geographic data using geopandas, xarray Financial knowledge is a plus but not required This organization is an equal opportunity employer, valuing diversity as essential to success. Employees are empowered to work openly and respectfully to achieve collective success. In addition to professional achievement, initiatives and programs are offered to help employees maintain a healthy work-life balance.
Negotiable
Zurich
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Quant Developer (m/f)
Qualifications Master's degree in Physics, Mathematics, Computer Science, or equivalent, with top grades* Proficient in various programming languages - Python & C++ preferred Comfortable with Linux/Unix (command line, SSH) Experience with version control (e.g., Git) Precise coder with strict coding practices Team player with clear communication Proactive, flexible, and stress-resistant *Minimum requirements: Top 200 university Top-tier grades (e.g., CH: >5.5, UK: >70%, NL: >8.0, DE: <1.6, FR: A, IT: 110L or equivalent) Benefits Competitive pay, including discretionary bonus Inspiring work environment Experienced colleagues 25 vacation days Commuting expense allowance Perks: regular dinners, Friday drinks, office trips, weekly massages, gym subscription, and free lunch
Negotiable
Zug
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Experienced Intraday Equities Researcher
Position: Experienced Intraday Equities Researcher About the Role: We are seeking a skilled Intraday Equities Researcher with 4+ years of experience on either the buy-side or sell-side, preferably with exposure to US or EU markets. This role is ideal for candidates who have demonstrated expertise in short-term prediction horizons ranging from 30 minutes to 1 day and have experience driving strategies from research to monetization. The right candidate will be joining a fund with over ยฃ15 billion in assets within an experienced, established team. The team has a track record >6 years and is looking for someone to seamlessly join their operation and immediately have a positive impact on the team. It is an opportunity for candidates to gain full ownership of the alphas they generate and work under a PM with a proven track record spanning over 10 years at several top tier firms. The pod is highly collaborative and with a h focus on a highly technical background. Key Responsibilities: * Develop and refine predictive models for intraday equity trading. * Transition insights into actionable strategies, taking them from research to production-level infrastructure. * Collaborate on building and optimizing the infrastructure necessary to support a scalable intraday trading business. * Leverage your understanding of the full lifecycle-from signal development to execution and monetization. Requirements: * 4+ years of experience in equities research, trading, or quantitative strategy development on buy-side or sell-side. * Strong familiarity with US/EU equity markets and intraday trading dynamics. * Proven track record in short-term prediction modelling (30 mins to 1 day horizons). * Hands-on experience with productionizing research and implementing trading infrastructure.
Negotiable
London
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Quantitative Researcher - Equities, Machine Learning - Paris
A multi-billion $ AuM Systematic Hedge Fund are looking to fill a senior role in its Equity Quant Strategies Group The Equity Quant Strategies Group oversees a portfolio of external hedge funds and develops proprietary absolute return strategies. In addition, the group is developing capabilities for quantitative, factor-based evaluation of external managers and optimal capital allocation across external hedge funds, internal strategies, and equities strategies. RESPONSIBILITIES Develop and continuously improve equity trading strategies Back test and implement trading models and signals in a live trading environment Use unique data sources to drive innovation Conduct statistical analysis to research and refine trading signals REQUIREMENTS 3+ years' experience Advanced training in Mathematics, Statistics, Physics, Computer Science, or another highly quantitative field Strong knowledge of machine learning, time-series analysis, pattern recognition, or NLP Background working in a data driven research environment Experience with analytical packages (e.g. Matlab, Python, R)
Negotiable
Paris
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Systematic Equity Sub-PM
A Multi-Strategy Hedge Fund in NYC is looking for a Systematic Equity Sub-PM to join their quant platform in 2025. The firm is looking for someone with a proven record in delivering consistent, new alpha across US, EU and/or APAC equity markets. The bolster the Sub-PMs research, the firm has spent several years developing top-tier research and trade infrastructure, procured dozens of datasets for alpha signal generation and provide exceptional execution services to drive PnL. The Sub-PM will work under one of the top-performing PMs within the fund who can further assist on mentorship towards a stand alone function. In addition to guidance, the Sub-PM will also be offered a sizable allocation, PnL split for their strategies and support from centralized teams. The ideal candidate for this role will have: 4-10 years alpha generating experience focused on mid-frequency horizons (intraday-days-weeks) Applied experience in portfolio construction and optimization Exposure to risk management Bachelors, Masters of PhD in STEM discipline Strong coding experience in Python *Important to note that the team is open to candidates with exceptional alpha generating experience coming from a centralized firm.
US$500000 - US$800000 per year + PnL split
New York
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Software Engineer, NLP/LLM
The signals team at an elite quant trading start up that focus on systematic strategies, are seeking a Senior NLP/LLM Engineer to join a small team of three. The role consists of partnering with quantitative researchers to enhance the data ingestion process. Simply, the function of the role is looking into how the firm can generate signals and data to send to researchers and make more money! The firm are highly machine learning and AI driven and are looking to scale those teams with elite talent. You do not need prior finance experience for this role, they are looking for exceptional technologist and are happy to train you up on the industry! This quant trading firm are in start up mode and have been spun out of one of the most successful quant trading groups in history. The firm has been founded to offer a flatter and more collaborative environment for talented and experienced individuals to thrive. They are looking to pay at the very top of the market range and keen to start interviews. This is a totally new area of the business, so they are looking for someone who can come in a spearhead the projects. Requirements: 4+ years post graduate industry experience Expertise coding in Python Experience with NLP/LLM Experience enhancing data processing Ability to collaborate with quant researcher
US$400000 - US$1000000 per year
Manhattan
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Quant Researcher - Macro Volatility
We are working with a rapidly growing hedge fund in NYC that is looking to bring on a Macro Volatility Quantitative Researcher to continue the expansion of their Macro desk. This person will conduct alpha research within the Macro Vol space and contribute to the existing suite of volatility models. Responsibilities Research and analyze volatility data Develop, deploy, and monitor models which trade in financial markets Evaluate and improve existing quantitative models Generate new ideas for additional research Promote best coding practices Requirements Graduate degree in computer science, math, physics, engineering, finance, economics or other related quantitative/analytical field from a top college or university Industry experience in researching macro volatility trading strategies and generating alpha Experience developing volatility models to support a trading desk Proficient in Python or another equivalent language Extensive knowledge of financial markets
US$150000 - US$225000 per year + Bonus
New York
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Systematic Equities - Sub Portfolio Manager
Systematic Equities - Sub Portfolio Manager New York, NY About the Client: Our client is a market-neutral, global equity multi-manager hedge fund with over $5 billion in assets under management. They are seeking an experienced Systematic Sub-Portfolio Manager, with a strong background in US Equities. The ideal candidate will have a deep understanding of Equity L/S markets in systematic teams, and have a proven track record of managing risk. This is a long-term potential hire for the team and whilst day 1 money might only be available for certain candidates, there is potential for anyone successful in the role to 'graduate' into a risk-taking PM seat in the future. Key Responsibilities: Assist a Systematic Equity Portfolio Manager in the development and execution of investment strategies. Monitor and manage portfolio risk, ensuring adherence to risk management guidelines. Conduct in-depth quantitative and qualitative analysis to support investment decisions. Collaborate with the research team to identify and evaluate new investment opportunities. Prepare detailed reports and presentations for internal and external stakeholders. Qualifications: Proven experience in a similar role within a hedge fund. Strong track record of managing risk and achieving positive PnL. Excellent analytical and quantitative skills. Proficiency in programming languages such as Python, R, or MATLAB. Strong communication and presentation skills. Ability to work effectively in a fast-paced, collaborative environment.
US$200000 - US$500000 per year
New York
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Quantitative Researcher - eFX
This team specialises in the electronic trading of FX swaps and forwards, leveraging advanced quantitative techniques to enhance market-making strategies and drive improvements in algorithmic trading. The ideal candidate will have strong expertise in quantitative research, coding proficiency in kdb+, Python, and Java, and a deep understanding of the FX swaps and forwards market. As a key member of this high-performing team, you will be responsible for conducting cutting-edge research in the FX swaps and forwards market-making space. You will work on a mixture of market-making strategies, algorithmic enhancements, and alpha research to support both principal and agency trading activities. The team operates at the forefront of statistical complexity, and you will collaborate closely with traders and quants in a high-calibre research-driven environment. Key Responsibilities: Market Making Strategy Development: Design and implement innovative market-making strategies for FX swaps and forwards, optimising pricing, liquidity provision, and execution in fast-paced, competitive markets. Algorithm Improvement: Work on enhancing existing algorithmic trading models and optimise their performance by incorporating novel quantitative techniques, improving execution efficiency and risk management. Alpha Research: Conduct in-depth research to identify new alpha signals and trading opportunities, integrating them into the trading system to improve profitability and competitiveness. Quantitative Analysis: Perform advanced statistical analysis, backtesting, and modelling of trading strategies, leveraging historical market data to develop robust models. Collaboration: Work closely with other quants, traders, and technology teams to integrate research findings in order to ensure seamless execution of trading strategies. Data-Driven Decision Making: Utilise large-scale market data and real-time trading information to guide decisions, providing a quantitative basis for trade execution and strategy adjustments. Continuous Improvement: Contribute to the development of cutting-edge techniques and methodologies in quantitative research and algorithmic trading to maintain a competitive edge in the eFX market. Key Requirements: Experience & Expertise: Experience (typically 3+ years) in quantitative research or electronic trading within FX swaps and forwards. Strong knowledge of FX market, market-making and trading strategies. Familiarity with principal and agency trading models, as well as their application in the FX space. Technical Skills: High-level proficiency in kdb+ (Q) and Python, with solid experience in Java. Strong background in statistical modelling, time series analysis, and high-frequency trading data. Familiarity with quantitative finance libraries, data analysis techniques, and backtesting platforms. Mathematical & Statistical Skills: In-depth understanding of advanced statistical methods, machine learning techniques, and time-series analysis as applied to quantitative trading and market-making. Expertise in model calibration, risk management, and optimisation techniques. Educational Background: A Master's or PhD degree in a quantitative discipline such as Mathematics, Statistics, Computer Science, Physics, Engineering, or Finance. Soft Skills: Strong analytical, problem-solving, and communication skills. A team player with the ability to collaborate effectively with traders, other quants, and technology teams in a fast-paced environment.
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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