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Quantitative Analyst

Job in 6340, Baar, Kanton Zug, Switzerland
Listing for: enshift AG
Full Time position
Listed on 2025-12-14
Job specializations:
  • Engineering
    Mathematics, Artificial Intelligence
Salary/Wage Range or Industry Benchmark: 80000 - 100000 CHF Yearly CHF 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Drive the energy transition by providing sustainable technological solutions through our digital platform, facilitating from planning to contract tendering to implementation of renewable energy systems in real estate and industrial companies. We enable our customers to increase the economic efficiency and CO2 balance of their properties while minimizing technical, commercial, and energy risks.

Tasks
  • Develop and improve advanced time-series forecasting models and optimization algorithms that power our Energy Management System.
  • Apply advanced mathematical and portfolio optimization techniques to allocate and schedule assets and associated operation models.
  • Analyze local energy market datasets to identify trends, pricing signals, and structural patterns for strategic decision making.
  • Build and enhance multi-model machine learning and AI frameworks to improve price forecasting and optimizations.
  • Implement and calibrate energy market prediction and risk models, including valuation and scenario analysis.
  • Ensure data and model reliability through automated testing, monitoring, and continuous refinement.
Requirements
  • Degree in Mathematics, Physics, Engineering, Energy Science, Computer Science, Quantitative Finance, or a related field. (Master’s or PhD welcome, but not required.)
  • Minimum 2 years of experience or exposure to mathematical optimization, data analysis, or modeling, ideally in energy-related environments.
  • Familiarity with machine learning concepts or risk modeling approaches.
  • Interest or experience in the international renewable energy markets.
  • Fluent in English
Benefits
  • An attractive salary package and exciting development opportunities
  • Further training in renewable energies and project management
  • A dynamic, innovative environment with short decision-making processes and plenty of creative freedom
  • The opportunity to play an active role in the energy transition and make a real impact
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