Lead Quant Developer - Renewable Energy

As Lead Quant Developer, you will translate quantitative research into production-grade trading systems for a growing renewable energy business. You’ll lead cross-functional collaboration to shape the tech roadmap and scale the trading platform across European markets. Expect hands-on work building forecasting, optimization, and automated dispatch capabilities while establishing robust model validation, deployment, and monitoring standards. This is a high-impact role shaping the technology frontier of energy trading with direct exposure to senior leadership.

• Salary up to 200k (negotiable)
• Bonus / profit share
• Equity
• Pension
• Impactful role

• Lead development of forecasting, optimisation, algorithmic bidding and automated dispatch systems
• Translate quantitative research into production trading strategies and live deployment
• Improve deployment speed, automation, and production reliability
• Establish standards for model validation, deployment, monitoring and incident response
• Define technology roadmap and build processes and team to scale trading tech
• Collaborate with Quantitative Research, Trading, Data, Engineering and AI teams
• Identify bottlenecks and evaluate build-versus-buy decisions to maximize value
• Lead the function as trading capabilities scale and expand into European markets

• Experience leading quantitative production/algorithmic trading technology in power/energy trading
• Experience taking quantitative models from research to production
• Strong software fluency with Python-based quantitative workflows, architecture and deployment
• Experience with production ML or model platforms, data-intensive systems and live monitoring
• Understanding of optimisation, automated bidding, dispatch or execution systems
• Sound commercial judgement to prioritize technology investment based on measurable value
• Experience leading cross-functional technical teams and managing external partners
• Hands-on, collaborative leadership style that fosters production discipline without stifling innovation
• BSc from a top-tier university

• collaborative leadership
• commercial judgement
• prioritisation under value-driven constraints
• Python-based quantitative workflows, architecture and deployment
• production ML or model platforms
• data-intensive systems and live monitoring