Senior Quant Risk Modeller (all)

BKW AG; Bern; Vor Ort; CHF 140.000 - 190.000; Vollzeit

Zusammenfassung

BKW AG in Bern invites a Senior Quant Risk Modeller to integrate quantitative risk and valuation models for trading, asset portfolios, and group risk topics across energy markets. You will develop stochastic power price models, calibrate and backtest models, and work with traders, originators, analysts, and risk managers to deliver transparent, robust solutions and governance.

Join a team building scalable analytics and reporting tools to support risk committees and leadership in a dynamic

Qualifikationen

• Experience in quantitative modelling, risk management, or commodity trading in energy markets.
• Hands-on history building risk, pricing, or valuation models in fast-moving markets.
• Ability to analyse dynamics across power, gas, and other commodity markets.
• Strong Python and SQL skills with modern analytical practices.

Aufgaben

• Develop quantitative risk and valuation models across assets and portfolios.
• Create stochastic power price models for energy and commodity markets.
• Calibrate, backtest, and benchmark models with governance.
• Collaborate with traders, originators, analysts, and risk managers on valuations.
• Prepare insights for Risk Committees and senior management.
• Contribute to scalable modelling, data, and reporting solutions.

Kenntnisse

Quantitative modelling

Risk management

Python

SQL

Stakeholder communication

Team collaboration

Tools

Python

SQL

Jobbeschreibung

BKW offers forward-looking total solutions in the areas of energy, buildings and infrastructure - internationally and in partnership. With around 12,000 employees, we build modern grids, generate renewable energy and realise energy-efficient buildings. We are looking for passionate people to join us in making a contribution to the society and environment of tomorrow. Become part of the BKW network and join us in creating living spaces worth living in!

Senior Quant Risk Modeller (all)

80-100%

You combine quantitative depth with practical market understanding and develop robust risk and valuation models for trading, asset portfolios, and Group-wide risk topics across dynamic energy and commodity markets.

Your field

• You further develop quantitative risk and valuation models across asset, trading, and sales portfolios as well as broader Group risk topics
• Developing stochastic power price models and quantitative approaches for complex energy and commodity markets forms a key part of your day-to-day work
• You ensure regular calibration, backtesting, and benchmarking of models with a strong focus on transparency, robustness, and model governance
• Together with traders, originators, analysts, and risk managers, you contribute to market-consistent valuation approaches and risk assessments for complex portfolio positions
• Quantitative insights and risk analytics are prepared by you for Risk Committees, senior management, and other key stakeholders in a clear and actionable way
• You help shape scalable and maintainable modelling, data, and reporting solutions while contributing to the evolution of the analytical tech landscape

What you bring to the role

• Several years of experience in quantitative modelling, risk management, or commodity trading within energy markets provide the foundation for your contribution
• You have hands-on experience developing and implementing risk, pricing, or valuation models in fast-moving market environments
• Complex dynamics across power, gas, and broader commodity markets can be analysed by you in a structured and commercially relevant way
• Strong Python and SQL skills, combined with modern analytical and software engineering practices, allow you to build robust quantitative solutions
• You navigate evolving technologies, processes, and market requirements with a pragmatic and solution-oriented mindset
• Collaboration across quantitative, commercial, and risk-focused teams comes naturally to you, and you communicate confidently with both technical and non-technical stakeholders