Asks for

The ad says“Proficiency in Python and software engineering practices: testing, code quality, code review, CI/CD, monitoring, and modular code design”
The ad says“Proficiency in Python and software engineering practices: testing, code quality, code review, CI/CD, monitoring, and modular code design”
The ad says“Proficiency in Python and software engineering practices: testing, code quality, code review, CI/CD, monitoring, and modular code design”
The ad says“Strong knowledge of probability and statistics, incl. time-series data processing, analysis, and forecasting, with a focus on streaming settings”
The ad says“Deep understanding of trading mechanics: price formation, market microstructure, risk, and the constraints that turn a backtest into a live strategy”
The ad says“Proficiency in Python and software engineering practices: testing, code quality, code review, CI/CD, monitoring, and modular code design”
The ad says“Proficiency in Python and software engineering practices: testing, code quality, code review, CI/CD, monitoring, and modular code design”
The ad says“Deep understanding of trading mechanics: price formation, market microstructure, risk, and the constraints that turn a backtest into a live strategy”
The ad says“Strong knowledge of probability and statistics, incl. time-series data processing, analysis, and forecasting, with a focus on streaming settings”
The ad says“Proficiency in Python and software engineering practices: testing, code quality, code review, CI/CD, monitoring, and modular code design”
The ad says“Deep understanding of trading mechanics: price formation, market microstructure, risk, and the constraints that turn a backtest into a live strategy”
The ad says“Proficiency in Python and software engineering practices: testing, code quality, code review, CI/CD, monitoring, and modular code design”
The ad says“Strong knowledge of probability and statistics, incl. time-series data processing, analysis, and forecasting, with a focus on streaming settings”
The ad says“Proficiency in Python and software engineering practices: testing, code quality, code review, CI/CD, monitoring, and modular code design”
The ad says“Strong knowledge of probability and statistics, incl. time-series data processing, analysis, and forecasting, with a focus on streaming settings”
The ad says“Deep understanding of trading mechanics: price formation, market microstructure, risk, and the constraints that turn a backtest into a live strategy”

Short Facts

• Location: Munich, Germany

• Employment Type: Full-Time, indefinite term

• Salary Range: € 95,000 – 115,000 per year gross, depending on seniority level

• Office First work setup

• Language Requirement: C1 Level English

Your Role

We are looking for a Quantitative Developer to tackle the software, data, and integration challenges across our Virtual Power Plant (VPP) ecosystem.

You will drive and own the roadmap for developing algorithmic execution strategies in the German intraday power market. As our VPP infrastructure matures, you will steadily increase your focus on research on execution-price improvement and market-impact modelling.

Your software-engineering work will centre on architecture design, testing, and project coordination.

Your Responsibilities

Contribute to the technical vision for how Flexa trades flexibility across energy markets and hardware assets, and help make it a reality
Identify new market opportunities and residential flexibility value to shape the data science roadmap and next-gen algorithms
Champion engineering rigor and best practices to foster an open, data-driven engineering culture.
Implement, deliver, and monitor well-engineered, data-driven solutions in our real-time production systems
Be part of a cross-functional team of data scientists, software engineers, and other teams across Flexa's partner ecosystem
Research, develop, and productionise algorithms and models that optimise financial returns from trading the flexibility of Flexa’s residential battery portfolio
Drive the delivery of complex, trading strategy projects from research to production deployment and monitoring — anticipating dependencies and resolving them early
Opportunity to guide and develop more junior colleagues through design review, code review, and structured feedback

Your Profile

Mandatory Requirements

University degree in a data-driven or analytical field (Computer Science, Mathematics, Physics, Statistics, or a related quantitative discipline)
5+ years applied data science and/or quant experience, with significant time spent developing trading algorithms in the energy or financial sectors
Proficiency in Python and software engineering practices: testing, code quality, code review, CI/CD, monitoring, and modular code design
Cross-functional collaboration mindset across data scientists, software engineers, and partner-company stakeholders
Deep understanding of trading mechanics: price formation, market microstructure, risk, and the constraints that turn a backtest into a live strategy
Strong knowledge of probability and statistics, incl. time-series data processing, analysis, and forecasting, with a focus on streaming settings
Excellent English communication and interpersonal skills
Independent research experience, excellent analytical skills with strong attention to detail, and the ability to manage multiple tasks in a fast-paced team environment are essential.

Skills to Set You Apart

Experience designing or owning real-time or near-real-time analytics workflows
Direct experience with energy trading, especially for the flexibility of battery storage systems
Expertise in designing algorithmic trading strategies and modelling market impact within intraday continuous markets
Substantial background in forecasting intraday price movements, modelling order book dynamics, and market microstructure
Experience with both Machine Learning and mathematical optimization development
Proven track record of taking models from research into reliable production on AWS (or comparable cloud)

At Flexa, we are committed to diversity — of backgrounds and experiences. You don’t need 100% of the listed requirements to apply.

Benefits

Virtual Share Options: we offer virtual share options to all our employees
Professional Development: annual development budget of €3,000 for coachings, trainings, books, and similar
Health & Sport Subsidy: company-subsidised sports facilities membership, or Public Transportation Subsidy
Lunch/Dinner Allowance Vouchers: allowance for meals on working days as digital meal vouchers
Work Equipment: MacBook or Windows laptop, iPhone (also for private use), and an ergonomic workplace setup with company-funded access to leading AI developer tools
Regular Team Events: knowledge sessions, afterwork, sports, offsites, Halloween, Pride Month, and more

A Short Note from Your Future Lead

Willi Richert, VP of Technology — flexa

Hi there!
I'm Willi, VP of Technology at flexa. I've spent the last 15 years building engineering teams around systems that have to make good decisions fast and at scale. Most recently at Lyft, where I led the mapping organization — 30+ engineers across five countries — and we moved more than 96% of rides off Google Maps onto our own mapping product. Before that I worked on machine learning and conversational AI at Microsoft Bing, and I did a PhD on learning in heterogeneous robot groups, which is a long way of saying that distributed decision-making has held my attention for a while.

What pulled me to flexa is that it's the same class of problem with something physical at the other end. We dispatch energy of the Enpal customer fleet in real time against energy markets. If our infrastructure is a few seconds late or a few percent off, customers lose money and the grid gets less flexibility than it could have had. That makes cloud engineering a first-order product concern here rather than a supporting function — which is why this role sits close to the decisions that actually matter.

How I work: I'd rather hand you the whole problem, context and constraints included, than a ticket. I care that engineers can see the consequences of what they build, and I'll be direct with feedback and expect the same back — the fastest way to lose a year is for everyone to stay polite about an architecture that isn't working.

You won't find everything already built. Some of it is greenfield, some of it needs replacing, and you'll have real influence over which is which. If that sounds like your kind of problem, I'd like to hear from you — and if you're not sure your profile is a perfect match, apply anyway and let's talk.

Looking forward to meeting you,
Willi