Staff Quantitative Researcher – Energy Trading (f/d/m)

Short Facts

Join us on our journey at Entrix: We are looking for an experienced Quantitative Researcher to shape how we trade flexibility from our customers' battery assets across European power markets. We operate in markets that run 24/7 (DAA, IDC, aFRR, and others), meaning every model decision we make turns into real positions, real risk, and real revenue. In this role you will guide the next generation of algorithmic trading at Entrix to keep us at the forefront of innovation. Sitting at the intersection of quantitative research and applied data science, you will own the alpha generation pipeline behind our algorithms, from signal research and

backtesting through to live trading and P&L attribution.

This is a staff-level individual contributor role where you will spend your time on the hardest problems in the team: framing ambiguous trading challenges, designing systems that combine machine learning and optimization to deliver impactful results, and mentoring data scientists to raise the bar across the team. As one of the most senior members of the team, you will own the technical vision for our trading algorithms, help drive the team roadmap, and mentor a strong group of individual contributors working on the hardest problems in the European energy transition.

• Location: Munich, Germany
• Employment Type: Full-Time, indefinite term
• Salary Range: € 115.000 - 135.000 per year gross depending on the seniority level
• Office-first work setup
• Language Requirement: C1 Level English

Your Responsibilities

• Shape the technical vision and roadmap for our algorithmic trading stack, breaking that vision into work the team can deliver, communicating trade-offs, and driving alignment on methodology, success metrics, and system design.
• Research, develop, and productize forecasts and strategies that generate alpha by trading flexibility in real-time European energy markets (DAA, IDC, aFRR, etc.), combining ML and optimization techniques to make 24/7 trading decisions.
• Enhance our the backtesting, simulation, and P&L attribution capabilities that turn research into live strategies, with rigorous overfitting controls, risk-adjusted evaluation, and automated testing.
• Foster technical excellence across the team by mentoring data scientists through design and code review, and by championing engineering rigor in code quality, observability, and reproducibility.
• Own the delivery of complex, ambiguous projects from research to production.

Your Profile

Mandatory Requirements

• 7+ years industry experience in quantitative research or applied data science, with significant time developing live trading algorithms in energy or financial markets.
• Proven track record of P&L contribution from strategies you researched, backtested, and shipped to live trading.
• Deep understanding of trading mechanics: price formation, market microstructure, execution, slippage, risk, and position sizing.
• Strong fundamentals in time series modelling under non-stationarity and regime shifts, with disciplined backtesting practice (risk-adjusted metrics, overfitting controls, walk-forward validation).
• Strong expertise in python and software engineering practices: testing, code review, CI/CD, monitoring, modular code design, and taking machine learning and/or optimization models from research into production systems.
• Track record of mentoring junior team members and raising the technical bar of the team.
• University degree in Computer Science, Mathematics, Physics, or a related quantitative field.

Excellent English communication and interpersonal skills.
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Skills to Set You Apart* Direct experience trading battery storage, flexibility, or other assets in European power markets.

• Experience combining machine learning (forecasting, signal generation) with mathematical optimization (LP, MILP, stochastic) in a single production-level system.
• Experience with financial