Quantitative Researcher


ID : 3210009

About Trailstone

At Trailstone we believe in shared success for our investors and our employees. Success is driven by exceptional people working together as a team with a passion for the mission and common values.

Trailstone is a global energy trader and risk manager. Our mission is to play a leading role in facilitating the worldwide transition to renewable power. Our primary business is real-time management of electricity generation assets. Our team of traders, meteorologists, software engineers, risk managers, and data scientists aim to increase the stability of electric grids while minimizing risk for generators of intermittent electricity from wind and solar investments. Trailstone leverages its energy market experience and predictive modelling platform to take and manage financial trading risk in energy markets.

Trailstone operates and develops a platform to trade renewable electricity assets like wind and solar power plants in Europe and North America. Today our robotic, AI & ML-driven real-time order execution manages thousands of renewable electricity assets.

About the Role 

As a Quantitative Researcher at Trailstone, you will play a central role in our mission of making sustainable energy truly sustainable. Within a close-knit team of researchers, commodity traders, and software engineers, you will develop and enhance systematic trading strategies, auction strategies, and risk-management frameworks for commodity markets around the world, with an eye towards the growing impact of renewable energy generation.

To build and maintain our edge, your work will require you to not only implement good statistical and machine-learning modeling practices, but to make high quality contributions to our internal analytics libraries and our global research platform. This role will challenge you to develop creative, customized solutions, as well as to commit to the continuous seeking, learning and sharing of new techniques and frameworks.

Essential Qualifications

  • Degree in a quantitative field (e.g. Mathematics, Computer Science, Statistics, Physics, Electrical Engineering) or relevant working experience
  • A firm understanding of core concepts and methods in probability, statistics, and optimization
  • Practical experience applying statistics and/or machine-learning to problem solving
  • Strong computer programming skills
  • Keen interest in commodity markets and trading
  • Excellent communication skills: able to convey a point concisely and deal constructively with conflicting views

Advantageous Qualifications

  • Masters or higher in a quantitative field
  • Demonstrated capacity to do first-class research
  • Expert level experience with Python, including the use of numerical libraries such as NumPy and pandas
  • Academic or industry-related knowledge of power markets
  • Experience in a front office quantitative analysis role (e.g., hedge fund, investment bank)
  • Experience with Python libraries for statistics (e.g., statsmodels, SciPy)
  • Experience with Python libraries for machine learning and/or artificial intelligence (e.g. scikit-learn, Tensorflow, or Pytorch)
  • Proponent of software engineering techniques and methods: version control, agile development, continuous integration, code review, unit testing, refactoring and related approach.

We’re different, and we like it that way! 

Here at Trailstone, we value our differences. In fact, our success depends upon them. 

Differences in backgrounds, identities and experiences lead to differing views of the world.  Different world views lead to healthy differences in opinions. Different opinions are essential to creating a robust marketplace of ideas. And it is our ideas that will make Trailstone a market leader in energy innovation and disruption! 

By our commitment to a diverse and inclusive workforce, Trailstone is creating value for our employees, our investors, and our communities. 

So regardless of your gender, race, ethnicity, orientation, physical limitations, how you identify, how you pray, who you love, where you went to school, who you consider family, or how old you are… you can belong here!