Risk Analytics Associate

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.

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.

• 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
• Monitor portfolio risk and limits, identifying emerging risks and escalating issues where appropriate
• Ensure full documentation and reproducibility of models and analytics

• Work closely with Tech and Data Engineering teams to improve the analytics platform, focusing on data quality, reconciliation, and scalability
• Standardise and automate analytics and reporting outputs to improve efficiency and consistency
• Structure and harmonise heterogeneous datasets into consistent portfolio-level views

• Be a cross-functional partner to teams to support portfolio construction, origination assessment, investor relations, and strategic initiatives
• Action reports for regulatory, audit, and governance processes

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.

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.

• 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
• Monitor portfolio risk and limits, identifying emerging risks and escalating issues where appropriate
• Ensure full documentation and reproducibility of models and analytics

• Work closely with Tech and Data Engineering teams to improve the analytics platform, focusing on data quality, reconciliation, and scalability
• Standardise and automate analytics and reporting outputs to improve efficiency and consistency
• Structure and harmonise heterogeneous datasets into consistent portfolio-level views

• Be a cross-functional partner to teams to support portfolio construction, origination assessment, investor relations, and strategic initiatives
• Action reports for regulatory, audit, and governance processes

• At least 2 years of experience in data analytics within private credit, asset-backed finance, securitisation, or related fields
• Understanding of ABF / securitisation fundamentals, including collateral analysis, portfolio monitoring, and structure mechanics (e.g. waterfalls, triggers)
• Advanced Python, (especially Pandas)…