About Fasanara

Founded in 2011, Fasanara is a global asset manager and technology platform.

We manage c. USD 6 billion AUM (as of December 31, 2025) in Fintech strategies on behalf of pension funds and insurance companies in Europe and North America.

With c.110 employees globally, we are a pioneer investor in Fintech Lending, enabling Real Economy Impact.

Fasanara manages the largest and longest standing Fintech Lending fund in Europe and invests in early-stage Fintech companies via its venture capital vehicles, using its central role in the Fintech ecosystem to identify and back revolutionary new businesses.

Our Culture

We are strong believers in meritocracy, and we seek to reward people based on impact and excellence. There is no bureaucracy, typical of large organisations. The environment is collaborative, entrepreneurial, and trust based. We set ambitious goals, work extremely hard, stress the importance of teamwork, and adhere to the highest level of excellence in everything we do. We are only as good as our team. Thus, we are building the firm around exceptional talent.

The Role

The Risk Analytics Associate works on the development and delivery of portfolio risk analytics across Fasanara's Asset-Backed Finance (ABF) strategies. This role sits at the intersection of Risk, Investment, and Technology, translating complex portfolio data into actionable insights to support investment decisions, portfolio construction, and risk monitoring.

The position combines strong technical expertise in data analytics and modelling with a commercial mindset, supporting multiple stakeholders including Portfolio Management, Capital Markets, and Investor Relations. The role involves writing a lot of code for the analytics platform, and ensuring high standards of code and data quality, as well as scalability.

Responsibilities

• Contribute to the development of portfolio risk analytics across ABF strategies, including: concentration, exposure, performance tracking, stress testing, outlier investigations, monitoring tools, and reporting outputs.
• Ensure full documentation and reproducibility of models and analytics.
• Work closely with Tech and Data Engineering teams to improve data quality and reconciliation.
• Action reports for regulatory, audit, and governance processes.