Your team

Your role

• Experiment, develop, implement, and deliver high-quality algorithmic long-only and long-short investment strategies/solutions with the responsibility to discover systematic anomalies and carry out financial research on main asset classes (mainly equity).
• Be responsible for maintaining and enhancing existing quantitative models/strategies and managing and assessing various data sources (prices, fundamentals, economics, alternatives) to advise on selecting the relevant ones with high added value.
• Potentially apply state-of-the-art machine learning and artificial intelligence to real-world problems at financial institutions by extracting and visualizing insights from large datasets.
• Investigate whether large language models (LLMs) are a suitable source of financial advice to generate substantial improvements in the quality and timeliness of reactions to corporate events by using specific AI agents capable of perceiving environments and distilling relevant information from company balance sheets, prices, or financial reports to forecast stock prices.
• Present the results to the Quant investment team using appropriate methods (dashboards, reports, software prototypes, etc.).

Your profile

• Master’s student in Finance or Master’s degree from a top-tier university in a quantitative field (e.g., Statistics, Mathematics, Economics, Physics, Computer Science, Machine Learning, or Artificial Intelligence).
• Passionate about coding, financial markets and systematic investment strategies for alpha generation, with strong problem-solving skills.
• High proficiency in Python and the overall Python ecosystem, backtesting routines (e.g., Back Trader, etc.), simulation, and statistical techniques.
• A curious, highly motivated, eager-to-learn individual, with strong self-starting capabilities and attention to detail, who wants to stand out within a dynamic and highly close-knit quant team.
• Excellent written and verbal communication abilities to explain and convey messages about complex/technical quantitative issues in English. Fluency in French would be an added advantage.
• Must be resident in Switzerland.

• Previous exposure to financial data, research, and multi-asset algorithmic/smart beta investment strategies would be an advantage.
• Strong data mining and data analysis skills: demonstrated ability in applying statistical modeling, machine learning, and exploratory analysis to large structured datasets for anomaly detection, classification, segmentation, and clustering.
• Experience in managed database solutions and coding (e.g., Postgres SQL, Snowflake, etc).

Note

Diversity & Inclusion