Senior quantitative researcher Vacatures

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