Loann Brahimi
I am a data scientist and quantitative developer with over 8 years of experience in data analysis, engineering, and modeling, and 4 years of direct front-office exposure in trading environments.
About
I am a data scientist and quantitative developer with over 8 years of experience in data analysis, engineering, and modeling, and 4 years of direct front-office exposure in trading environments. I have worked as a systematic hedge fund trader/developer, a consultant to commodity trading firms, and a front-office software engineer for an electricity trading company. I design robust, data-driven decision systems that enhance operational efficiency and trading performance.
I specialize in cloud-based ETL pipelines, real-time dashboards, and the integration of machine learning into analytics workflows. I am comfortable running end-to-end projects—from data ingestion and model deployment to backtesting and production monitoring—and I thrive in fast-paced energy and financial markets.
- 9 years' experience
- Joined January 2026
Industry experience
- Financial Services
- Energy & Utilities
- Software & Internet
- Professional Services
- Other
More experts in Geneva, Switzerland
Work experience· 10 roles
Joined as the third employee at Improm AI, helping to establish processes, business model and initial product ideation. Led the design and deployment of cloud-based data pipelines and front-end analytics solutions to empower commodity trading teams with actionable insights. Collaborated with traders to translate business needs into robust, scalable analytics and AI workflows.
Supported traders with IT and analytics needs, standardizing processes and best practices. Built and maintained data analytics and front-office applications including a short-term power positions visualization tool (Flask REST API), a hedge-asset allocation framework for delta hedging strategies, a North gas forward curve management tool, data synchronization tasks, data scrapers, and an automated P&L computation tool.
Key member of a systematic hedge fund trading S&P 500 futures using a proprietary market sentiment algorithm. Led R&D on financial market patterns, statistical analysis, and ML-based approaches; built, deployed, and monitored ETL-based trading pipelines and a fully automated Portfolio Management System (PMS); oversaw middle-office operations and fund performance. Achieved +21.3% P&L in 2023.
Education
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