Quantitative Trading Analyst

We are Dexter Energy! We are an Amsterdam-based scale-up that’s building AI-based forecasting and optimization products in order to help renewable energy companies solve this problem. Our mission is to enable a sustainable and affordable power system that changes the energy market. We truly believe we can make a significant impact on climate change. Our software makes renewables more predictable and profitable, helping push fossil fuels out of the market, and speeding up the energy transition.

Power up our team

Our cross-functional trading optimization product teams are where innovation takes form. These teams develop and operate machine learning-powered software products that forecast electricity market prices and recommend optimized trading strategies to our customers for short-term energy trading on the day-ahead and intra-day markets.

This role is the watt you've been looking for!

As a Quantitative Trading Analyst in the product team, you play a pivotal role in designing, improving, expanding, and monitoring the optimized trading strategies for our customers.

Your responsibilities include:

• Developing, deploying, and monitoring automated trading strategies.

• Investigating new meteorological and energy market data sources and generating ideas for machine learning model input features to improve performance.

• Working on our automated backtesting framework to improve the validation of new trading strategies.

• Analyzing new markets and supporting the geographical expansion of our trading optimization products.

• Designing and prototyping new trading optimization products or product features.

• Monitoring and reporting on energy markets to identify trends that can impact product performance.

• Collaborating with data scientists to design, build, and validate machine learning-based forecasting and optimization models.

• Collaborating with software engineers to bring research results to production.

It’s time to amp up your career

Why should you consider this opportunity?

• Most of our work is truly greenfield. We have live products, but we'll be building many new features and services from the ground up.

• Be part of a clean-tech scale-up that has a positive impact on the environment.

• Join an ambitious, motivated, and entrepreneurial team with exceptional opportunities to grow.

• Experience a flat hierarchy environment where decisions are made quickly.

• Our salary and stock options are pretty good.

• Learn from extremely talented colleagues who are eager to share their knowledge.

• Work with large data volumes and modern technologies on the Google Cloud Platform.

• Balance work and life, with encouragement to plan work around your hobbies.

Here are the current requirements

To succeed in this role, you should have:

• A minimum of 3 years of experience in a professional short-term energy trading environment.

• An expert understanding of European short-term energy markets (day-ahead, intraday, and imbalance markets).

• Experience with setting up, validating, and analyzing algorithmic trading strategies, including backtesting.

• Proficiency with the Python data stack (e.g., pandas, scikit-learn, Jupyter).

• Strong motivation to build algorithmic trading software products instead of actually making trades or designing processes.

• Excellent communication skills, with a good command of the English language.

• Self-organized and able to work independently while collaborating proactively with others in the company.

• Ability to thrive in a fast-paced, dynamic environment.

• A passion for renewable energy and a desire to make a difference in the world.

Join Dexter Energy as a Quantitative Trading Analyst, where you'll harness the power of data to drive the renewable energy revolution.

Apply now and be part of an inclusive, innovative team that is shaping the future of sustainable energy.

Dexter is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity.