Quantitative Developer/Analyst; Medior/Senior
Listed on 2026-02-23
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IT/Tech
Data Engineer, Data Analyst, Data Scientist, Data Science Manager
Eneco is at the forefront of the energy transition integrating renewable generation, flexible assets, and new ways of balancing supply and demand. As energy markets become more volatile and interconnected, the need for smart risk management and data-driven decision-making only grows.
Our newly established Systematic Trading Desk develops and runs proprietary quantitative strategies to diversify Eneco’s market exposure. The desk also acts as a catalyst for improving and automating trading workflows across the other desks. As a front-desk Quantitative Developer, you’ll make sure that we have the necessary data and that we build tools that let systematic strategies move from idea to live trading and continuously improve.
As a front-desk Quantitative Developer, you will build and maintain the tooling, data foundations, and research/production workflows that allow strategies to be developed, tested, deployed, and monitored reliably. You’ll work closely with systematic traders and analysts, and collaborate with colleagues covering discretionary power, gas and carbon.
- Improve our trading strategy backtesting and optimization frameworks to support scalable runs, better performance metrics, and robust result storage/comparisons;
- Refine trading strategies through backtesting, tuning free parameters, scenario analysis, and sensitivity checks;
- Build analytical and real-time dashboards for traders (strategy status, run controls, key metrics, performance reporting);
- Analyze new market data sources, define data requirements, clean/validate datasets, and make them available for research and production use;
- Perform validation steps to make strategies production-ready: testing, monitoring, controls, documentation, and handover;
- Liaise with Compliance and Risk when needed to ensure appropriate controls, auditability, and sign-off;
- Liaise with IT teams to ensure the right infrastructure and connectivity are set up (data pipelines, databases, interfaces/adapters);
- Liase with Trade Operations teams to ensure proper interaction with deal capture and business reporting systems;
- Translate front-desk needs into clear technical requirements, and perform business testing (UAT) to validate solutions before go-live.
We’re looking for someone with solid quantitative development skills combined with experience in quantitative trading analysis.
- 4–5+ years (for Medior) of relevant experience in quantitative development / trading tooling / front-office analytics support, building production-grade code (Python). Senior role candidates will have substantial additional experience and end-to-end ownership;
- Highly valued: experience working directly with traders and front-desk analysts to translate needs into clear requirements and deliver workable solutions in a fast-paced environment.
- Solid understanding of financial markets—energy commodities preferred—and how a trading desk operates.
- Understands the core building blocks of a systematic trading strategy (signals/features, position sizing, constraints, execution logic, and monitoring).
- Comfortable with quantitative trading analysis: descriptive statistics, distributions, correlations, backtesting basics, and interpreting performance metrics (e.g., returns, drawdowns, Sharpe/Sortino, hit rate).
- Proven experience directly partnering with traders to translate business needs into clear technical requirements and workable solutions.
- Strong communication through visuals: produce clear, actionable dashboards and reports for traders.
- Strong Python skills with a focus on modular, performant, testable code.
- OO design, event-driven patterns, asynchronous programming; multithreading where relevant.
- Ability to build analytical and real-time dashboards using tools like Grafana, Power BI, or similar platforms.
- Experience with good software delivery practices:
Git, unit/integration/regression testing, and CI/CD pipelines. - Experience working with cloud-based platforms and scalable infrastructure (compute, storage, containers such as Docker/Kubernetes).
- Able to design/shape reliable real-time and historical market data pipelines, with strong attention to data…
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