(Senior) Quantitative Analyst / Trading Analyst, Autobidder

What To Expect
Join Tesla’s Autobidder Operations team and drive the future of energy trading. Autobidder, the leading platform for battery storage optimization, manages the world’s largest fleet of energy assets—from utility-scale batteries to virtual power plants. As a Senior Trading Analyst, you’ll refine algorithmic trading strategies, unlock revenue opportunities, and accelerate the global shift to sustainable energy.

What You'll Do

Lead analytical projects to refine trading strategies and algorithm development

Analyze electricity trading trends, competitor activity, and policy changes to identify revenue opportunities

Perform forensic analysis of trading outcomes to identify opportunities for algorithmic refinement

Develop and enhance Python-based tools, simulations and analytical workflows to evaluate battery fleet performance, validate strategic hypothesis and generate actionable insights

Collaborate with optimization and software teams to enhance algorithmic decision-making and scalability

Translate commercial questions into structured hypotheses, conducting simulations and backtesting to validate strategies.

Monitor European electricity markets to optimize battery storage monetization

Participate in on-call rotations to support real-time market operations and ensure system reliability

Communicate performance insights and market updates to internal teams, customers, and external stakeholders

Must be authorized to work in the UK

What You'll Bring

5+ years in an analytical, data science, or quantitative role, with a focus on energy markets, electricity trading, or energy storage optimization

Strong quantitative and energy trading experience is essential; familiarity with the UK energy market is a plus

Proven track record in data-driven decision-making, including statistical analysis, predictive modeling, and deriving actionable insights from large datasets

Experience designing and executing simulations, backtesting frameworks, or scenario analyses to validate trading strategies or market hypotheses

Expertise in translating complex business questions into structured analytical workflows, leveraging tools like Python (pandas, NumPy, scikit-learn) for data manipulation and modeling

Familiarity with machine learning applications in energy markets (e.g., price forecasting, demand prediction) or optimization techniques (e.g., linear programming, stochastic modeling)

Prior exposure to algorithmic trading environments, energy storage revenue stacking, or market design analysis

Fluency in English, any other European language is a plus

, Tesla