Quantitative researcher Vacatures

Over de vacature

We are looking for a Quantitative Researcher to join a team focused on the development of fully automated systematic trading strategies across global equity and multi-asset markets.

The role sits at the intersection of research and engineering, with a strong emphasis on generating alpha signals, building predictive models, and translating research ideas into live trading strategies. You will be involved in the full lifecycle of strategy development, from initial hypothesis generation through backtesting, implementation, and ongoing performance refinement.

Key Responsibilities

1. Research and design predictive signals for systematic trading strategies.
2. Develop and test quantitative models using large-scale financial datasets.
3. Apply statistical and machine learning techniques to identify market inefficiencies.
4. Collaborate with engineers and researchers to implement strategies into production systems.
5. Monitor and analyse live strategy performance, iterating to improve returns and robustness.
6. Contribute to research infrastructure and tools that support scalable strategy development.
7. Take ownership of research projects with clear focus on PnL impact and real-world performance.

Requirements

1. Degree in a highly quantitative subject such as Mathematics, Statistics, Physics, Computer Science, Engineering, or similar.
2. Strong grounding in probability, statistics, and machine learning methods.
3. Excellent programming ability in Python, C++, or Java, with experience working on real datasets.
4. Demonstrated interest in systematic trading, quantitative finance, or algorithmic modelling.
5. Ability to work independently while collaborating effectively in a high-performance team environment.
6. Strong analytical mindset with a focus on practical, data-driven results.

Preferred Experience

1. Previous internship or work experience in quantitative research, systematic trading, data science, or related fields.
2. Experience building and deploying predictive models in production or research environments.
3. Familiarity with noisy, non-stationary datasets and financial time series data.

Over de vacature

EKA Finance is working with an established quantitative trading firm looking to hire a Senior Quantitative Researcher into a highly research-driven trading environment.

The role is focused on developing systematic, short-horizon trading signals and strategies from idea generation through to live implementation.

We are particularly interested in researchers who have worked close to electronic markets and can demonstrate genuine ownership of quantitative research rather than purely execution or infrastructure work.

The Role:-

You will research and develop predictive signals and systematic trading strategies using high-frequency market data.

The work will involve:

1. Generating and testing new short-horizon trading ideas
2. Researching market behaviour and microstructure
3. Developing predictive features and signals from order-book and trade data
4. Building robust backtesting and validation frameworks
5. Working closely with trading and engineering teams to move successful research into production
6. Continuously analysing and improving live strategies

What We Are Looking For:-

Candidates are likely to have several years of experience in quantitative research within an electronic trading environment.

Relevant backgrounds could include:

1. Electronic market making
2. High-frequency trading
3. Short-horizon statistical arbitrage
4. Systematic trading research
5. Market microstructure research

You should have:

1. Strong quantitative and statistical research skills
2. Experience working with large, high-frequency datasets
3. Evidence of developing predictive signals or trading strategies
4. Strong programming ability, particularly in Python or another research-oriented language
5. A rigorous approach to backtesting, validation and avoiding overfitting
6. A genuine interest in understanding why trading signals work rather than simply optimising historical results.

Formal ownership of a standalone P&L is not required . We are more interested in researchers who can clearly demonstrate the contribution their research made to live trading strategies.

Experience within a market-making business can be particularly relevant, provided your work involved alpha generation and strategy research rather than purely execution, quoting or risk management.

This is an opportunity to take meaningful ownership of research within a growing quantitative trading business and work directly on strategies that can be deployed into live markets.

Over de vacature

Amsterdam

We are expanding our research organization and are looking for an experienced Senior Quantitative Researcher to join our Amsterdam-based team. This position plays a key role in shaping new research initiatives and carries responsibility for technical leadership, mentorship, and team development.

In this role, you will work on the discovery and productionization of machine-learning-driven trading strategies, while helping guide junior researchers and collaborating closely with trading, engineering, and infrastructure teams.

Your role

1. Creating, testing, and deploying machine-learning-based statistical arbitrage strategies in live trading environments
2. Identifying new sources of alpha through deep analysis of high-frequency market data
3. Developing features and predictive models across large universes of instruments over short-term horizons (seconds to minutes)
4. Building and maintaining scalable ML research and production pipelines across multiple venues and markets
5. Continuously improving existing models through rigorous evaluation and optimization
6. Acting as a key point of contact between research, trading, and engineering groups
7. Providing technical guidance, mentorship, and-where appropriate-line management to other researchers

What we are looking for

1. Five or more years of hands-on experience in a high-frequency or ultra-low-latency trading environment
2. Strong track record applying machine learning techniques to systematic trading strategies
3. Practical experience operating ML pipelines across multiple exchanges, both independently and in coordinated setups
4. Demonstrated ability to design and implement complex statistical arbitrage strategies across multiple instruments
5. Willingness to deepen expertise in high-frequency market dynamics and scale strategies across many trading venues
6. End-to-end ownership mindset, from raw data ingestion and feature engineering through to live deployment
7. Strong programming skills in at least one language; Python experience preferred
8. A self-driven, resilient, and highly engaged approach to problem solving
9. Ability to collaborate effectively with colleagues from diverse technical and academic backgrounds

Nice to have

1. Prior experience mentoring researchers, supervising interns, or leading small quantitative team

Over de vacature

We are a proprietary trading firm operating at the intersection of mathematics, technology, and global financial markets. From our Amsterdam office, we design and run systematic, low-latency trading strategies across multiple asset classes and venues worldwide.

Our researchers come from highly competitive academic and technical backgrounds, and we actively engage with the international problem-solving community. Many members of our team have distinguished themselves in mathematical research, engineering, and elite competitions.

We are currently expanding our trading research group and are seeking a Junior Quantitative Researcher to work closely with an active trading desk. In this role, you will study market behaviour at fine time scales and help design, test, and refine strategies that operate in live markets.

You will be part of a high-performance research environment where ideas move rapidly from analysis to production. The trading teams are backed by a dedicated infrastructure and engineering group, allowing researchers to focus on modelling, experimentation, and performance improvement without operational friction.

We operate with minimal hierarchy and place strong emphasis on ownership, intellectual curiosity, and open discussion. If you enjoy working in a collaborative setting where original thinking is encouraged and results are visible quickly, this role may suit you well.

What you will work on

1. Building and refining systematic trading models using statistical analysis and modern machine learning approaches
2. Investigating market microstructure and short-horizon price dynamics to uncover new sources of edge
3. Partnering with software engineers and fellow researchers to translate research into efficient, production-ready strategies
4. Supporting the ongoing enhancement of existing strategies and contributing to the broader research roadmap

What we are looking for

1. Academic training in a quantitative field such as mathematics, physics, computer science, or a related discipline
2. Strong foundations in probability, statistics, and quantitative reasoning
3. A track record of high achievement in mathematical or programming competitions (e.g. IMO, IOI, ICPC, IMC, Code Jam, Hash Code, Hacker Cup, or similar)
4. Solid programming skills in Python
5. Prior exposure to C++ (professional experience not required)
6. Familiarity with machine learning techniques is a plus

Over de vacature

I'm working with a fast-growing proprietary trading firm in Amsterdam looking to hire an exceptional Graduate Quantitative Trader .

This is aimed at candidates with outstanding quantitative ability , typically from a top academic or research background, who want to move into systematic trading.

Previous finance or trading experience is not required .

You'll join a small, highly technical team trading digital-asset markets using fully automated high-frequency strategies.

You'll work closely with experienced quantitative traders, researchers and engineers to:

• Analyse large, high-frequency datasets

• Research and test new quantitative trading ideas

• Identify patterns and opportunities in market data

• Help implement and optimise systematic trading strategies

• Monitor live algorithms and investigate trading behaviour

• Apply statistical and mathematical techniques to real market problems

• Help take research from initial idea through to production

Requirements

We're looking for candidates with:

• An exceptionally strong academic PhD background in Mathematics, Statistics, Physics, Computer Science, Econometrics, Engineering or another highly quantitative field

• Excellent Python programming ability

• Strong probability, statistics and mathematical modelling skills

• Excellent data-analysis and critical-thinking ability

• Evidence of solving difficult quantitative problems independently

• Strong attention to detail and communication skills

• A genuine interest in financial markets and quantitative trading

PhD candidates, researchers and exceptional graduates from highly quantitative programmes are particularly encouraged to apply.

No previous financial-markets experience is required.

Location: Amsterdam

Working model: Full-time, on-site

Asset class: Crypto / Digital Assets

Experience: Graduate / Early Career

Compensation: Above-market salary + performance bonus

Over de vacature

Overview

In this role you build and maintain pricing data systems used by traders and researchers across Optiver. You work at the intersection of pricing automation, quantitative research, and data platform engineering, delivering data products that enable new trading strategies. You will collaborate with traders, researchers, and platform teams to run live pricing pipelines and reproduce pricing over many years of history. This is a hands-on, impact-oriented role in a small multidisciplinary group that ships across C++/Python boundaries, with a strong emphasis on data quality, throughput, and long-term replay.

Arbeidsvoorwaarden / Benefits

• performance-based bonus
• global collaboration across 40+ countries
• 25 paid vacation days
• fully paid first-class commuting expenses
• training opportunities
• health insurance discounts

Verantwoordelijkheden

• Build and optimize live pricing systems that run continuously during the trading day
• Develop replay frameworks to reproduce production pricing calculations over years of historical data
• Integrate new external datasets into Optiver's pricing ecosystem to extend research capabilities
• Own production pipelines that compute and serve core pricing data
• Collaborate with traders, researchers and platform teams to deploy production systems
• Balance system throughput, schema evolution, and historical replay considerations
• Operate with an emphasis on monitoring, validation, and data quality

Belangrijkste vereisten

• Strong engineering fundamentals in computer science

• Proficiency in either C++ or Python and ability to work across the other language

• Experience designing distributed data systems and understanding throughput, schema evolution, and historical replay

• Exposure to data platforms (e.g., Delta Lake), cloud infrastructure, or large-scale data engineering is a plus

• Pragmatic delivery mindset and ability to navigate complex domains

• Collaborative with traders, researchers and other engineering teams

• Collaborative mindset

• Pragmatism

• Ability to turn ambiguous requirements into production systems

• C++

• Python

• ETL/ orchestration code

Over de vacature

I'm working with a fast-growing proprietary trading firm in Amsterdam that is looking to hire an Experienced Quantitative Trader into its crypto HFT business.

The firm trades systematically across digital-asset markets using fully automated, high-frequency strategies and a low-latency trading platform.

This is a hands-on role sitting between quantitative research, live trading and strategy implementation . You'll be expected to develop new trading ideas, analyse market behaviour, improve existing algorithms and take increasing ownership of strategies running in production.

The role:-

You will:

• Research and develop systematic trading strategies

• Analyse high-frequency market and order-book data

• Identify new trading opportunities and market inefficiencies

• Backtest and validate quantitative ideas

• Monitor and optimise live strategies

• Investigate trading performance, execution and market behaviour

• Work closely with traders and engineers to move research into production

• Take meaningful ownership of strategies and trading decisions

What we're looking for

Essential:

• Master's or PhD in Mathematics, Physics, Computer Science, Engineering, Econometrics or another highly quantitative subject

• Strong Python programming skills

• Strong statistics, probability and quantitative modelling ability

• Experience working in a systematic / quantitative trading or research environment

• Ability to develop and test trading ideas using real market data

• Strong analytical and problem-solving ability

• Willingness to work on-site in Amsterdam

Particularly interesting backgrounds:

• HFT / electronic market making

• Short-horizon systematic trading

• Statistical arbitrage

• Market microstructure research

• Cross-venue / arbitrage strategies

• Automated market making

• Quantitative trading across equities, futures, options or crypto

Previous crypto experience is helpful but not essential. Strong systematic traders/researchers from other liquid asset classes are very relevant if they are interested in moving into digital assets.

Experience with Rust, C++ or low-latency systems is advantageous but not required for the Quant Trader role.

Environment

This is a small, highly technical trading team where researchers, traders and engineers work closely together. It will suit someone who wants more strategy ownership and faster research-to-production cycles than they might get at a larger platform.

Location: Amsterdam

Working model: On-site

Asset class: Crypto / Digital Assets

Strategy style: Systematic / High Frequency / Market Making