About the role

AlgoTrading Product Owner responsible for managing data infrastructure for algorithmic energy trading at Brady Technologies. Designing trading models and supporting risk assessment frameworks in the energy market.

Responsibilities

You'll be responsible for defining our data structure and its initial set up, and designing and managing the data infrastructure for algorithmic energy trading including training, testing, backtesting and deployment of algo trading models.
You'll get to support the development of risk assessment and performance assessment frameworks of algorithmic strategies and develop a standardised algo backtesting framework to ensure the continuous improvement of our models.
The APO will be designing and performance testing the market leading Brady Edge Algo solution.
The APO will be designing and managing the functionality for algorithmic energy trading that will include training, testing, back testing, and deployment of algo trading models.
The APO supports the development of risk assessment and performance assessment frameworks of algorithmic strategies and the development of a standardised algo back testing framework that will ensure a continuous improvement of our models.
The APO is passionate about their work, enjoys working in cross-functional teams and learning from and teaching others on the journey to build world-class power-trading software.
The APO will be participating in furthering the research and development and research literature in the energy industry focused data science field by actively participating with the Lead Data scientist to publish in Energy journals of national and international scope.

European Short-Term trading modelling or trading experience
Experience in data processing with R and/or Python is desirable
Data mining, decision science and predictive analytics
Experience in algorithmic trading and quantitative modelling (modelling)
Understanding of time series data – storage, processing, aggregation, nesting, clock change conversion
Great attention to detail with ability to work independently and also as part of a team.
Knowledge of predictive algorithms for short- and long-term forecasting of time series, including time series with multiple seasonal cycles
Knowledge of various methods to assess accuracy of designed forecasting models, perform stress testing and scenario analysis
Knowledge of cloud infrastructure to some degree, namely MS Azure.
Experience of deploying data science solutions (including forecasting models) on the cloud infrastructure desirable.
Knowledge of a model development pipeline.

Great compensation + 5% bonus + private health insurance!
24 days' holiday + bank holidays
1/2 day off Christmas Eve & New Year's Eve
Pluralsight licenses for engineering team members
Flexible working hours
An opportunity to build a modern technology platform for the power and energy trading markets
A positive, values-driven culture