Quantitative Developer

A fantastic opportunity has arisen for a bright graduate with 2 years Quantitative Developer experience and Python development. This role hybrid with 2 days in the London office 3 days WFH.

As a Quantitative Developer you will play a critical role in designing, developing, and maintaining our scheme forecasting models and analytical tools, as well as the publication of supporting technical documentation. You will work closely with analysts and stakeholders within the wider business to gather requirements, driving projects from inception to deployment. You will leverage your expertise across object-oriented software engineering, quantitative modelling, cloud computing, and data analysis to help improve the models underpinning our most business-critical cashflow and pricing engines. You will come up with ad-hoc experimental analysis and scenarios to test energy market robustness within our numerical and statistical frameworks.

Great Benefits

• 25 days' annual leave and bank holidays
• Recognition schemes allowing colleagues to say thanks
• Company contribution to your pension scheme
• Family friendly policies, including enhanced company maternity/paternity and shared parental benefits
• Employee assistance programme for free, confidential support for your professional or personal life, including financial management and family care
• Special leave such as study leave, sabbatical or public duties
• Three days paid leave a year for volunteering to support your local community
• Season ticket loan scheme to support your commute
• Access to "Work Perks" offering deals, discounts and cash back on your purchases
• Family savings on days out and English Heritage or gym discounts through our partners.

The ideal candidate for the Quant Developer role will combine an understanding of energy market fundamentals with state-of-the-art algorithm building and optimisation techniques. They will be required to take on complex challenges with a sense of urgency and enthusiasm, developing and communicating insights in a clear and succinct way. Furthermore, the candidate should be adaptable and curious, with the ability to be versatile in technologies and approaches used, and a strong willingness to learn and develop.

Key Responsibilities As A Quantitative Developer

• Design and build short and long-term energy models in-line with best software engineering practices
• Manage, test and deploy both bug fixes and updates to existing models, validating and tracking development tasks in Jira and GitLab
• Work with analysts to gather requirements, design tests and scope new projects
• Create and update technical documentation
• Explore and clean datasets required for modelling purposes with a focus on optimising data pipelines
• Identify streamline and optimise inefficient processes
• Prepare and deliver presentations and visual materials that effectively communicate software design decisions and model logic to non-technical stakeholders

Skills Knowledge and Expertise As A Quantitative Developer

• A good first degree or higher degree in a highly numerate subject is essential
• Minimum 2 years' experience in Python development, including scientific computing and data science libraries (NumPy, pandas, SciPy, PySpark)
• Solid understanding of object-oriented software engineering design principles for usability, maintainability and extensibility
• Experience working with Git in a version-controlled environment
• Good knowledge of parallel computing techniques (Python multiprocessing, Apache Spark), and performance profiling and optimisation
• Good understanding of data structures and algorithms
• An enthusiastic problem-solving mindset with a desire to solve technical problems and model/forecast intricate real-life systems
• The ability to communicate complex technical concepts to those with little or no technical background in a meaningful, relevant and engaging manner
• Experience with cloud platforms desirable (Azure, AWS or GCP)
• Experience working with Machine Learning libraries (scikit-learn, PyTorch) and statistical techniques is desirable