Data Analyst H/F

Licorne Society

Licorne Society is a key player in connecting skilled professionals with dynamic FinTech companies. Tasked by a rapidly growing FinTech, they are on the lookout for a driven Data Analyst to assist in financial data management. This role is crucial in extracting, processing, and interpreting data, offering valuable strategic insights to their clientele.

In this role you can expect to have the responsibilities:

• Collect, clean, and analyze financial datasets from various sources like financial markets and client databases.
• Develop interactive dashboards and reports using Tableau to present financial insights.
• Collaborate with technical teams to optimize data integration and processing within the platform.
• Utilize programming languages such as Python and SQL for efficient data manipulation and analysis.
• Identify trends, anomalies, and opportunities from data and provide recommendations.
• Participate in the development of predictive models and algorithms to enhance data management processes.
• Ensure data quality and compliance while maintaining security in line with regulatory requirements.
• Work with commercial teams to meet institutional clients' specific needs.

This role requires you to have:

• Strong data analysis skills with proficiency in tools like Python, SQL, and Tableau.
• Good understanding of financial concepts and products such as stocks, bonds, and derivatives.
• Experience with databases and cloud environments.
• Excellent analytical skills with the ability to interpret complex data.

You would benefit from having:

• Ability to work autonomously while collaborating with multidisciplinary teams.
• Fluency in English and ideally other European languages.
• Clear communication skills to present results concisely and effectively.

Candidates are expected to have graduated from a top engineering or business school, or a recognized university with a specialization in finance, mathematics, statistics, or a related field. The role requires 2 to 5 years of experience in financial data analysis, preferably in an institutional environment. Candidates should be rigorous, organized, and possess a keen critical mind, with a strong passion for finance and new technologies.