Quantitative Credit Risk Analyst

About the Risk team

At Alma, the Risk team enables the company to grow fast and securely by anticipating, quantifying, and mitigating the risks that could impact our business. Our mission spans across several dimensions:

• Continuously improving our credit scoring models to offer a seamless payment experience, maximizing acceptance while protecting Alma from default risk and customers from over-indebtedness.
• Preventing and detecting fraud using data-driven techniques.
• Designing tools, methodologies, and processes to accurately assess the risk level of our merchants — at onboarding and throughout the customer lifecycle.

Within the Risk team, the Quant Analytics team plays a central role. We are responsible for:

• Developing and continuously improving our machine learning-based scoring models, and adapting them to new products, new markets, and changing customer behaviors.
• Building quantitative frameworks to support strategic decisions across the company.
• Monitoring, measuring, and reporting our risk performance and pricing accuracy.

About the job

Your role will be to drive the development of quantitative risk methodologies, with a strong focus on consumer credit risk, while also contributing to the assessment of merchant risk. You will:

• Improve and evolve our credit risk models

  Enhance our customer scoring algorithms using advanced machine learning techniques. You’ll help identify new data signals, explore model improvements, and adapt our approach to new products, customer segments, and geographies.

• Design impactful credit strategies

  Develop risk-based strategies to optimize margins and acceptance, identifying new levers to improve our risk-return balance.

• Monitor and project credit performance

  Build tools and methodologies to monitor the evolution of our credit risk metrics and explain key drivers. You will also design projection models to anticipate future P&L impacts and steer risk decisions.

• Contribute to merchant risk analysis and methodology

  Support the development of quantitative approaches to identify, monitor, and evaluate merchant risk, especially in relation to liquidity events and counterparty exposure.

• Collaborate cross-functionally

  Work with teams across Product, Data, Finance, and Operations to bring quantitative insights into decision-making and co-design robust, risk-aware solutions.

• Promote a data-driven risk culture

  Be a go-to expert on credit risk topics and help raise awareness of key risk-related issues across the organization.

About you

Your skillset:

• Fluent in English and French
• Strong Python and SQL skills : You’re comfortable manipulating data, building models, and automating analytical workflows.
• Solid background in credit risk modelling and financial analysis.
• Hands-on with machine learning : You have a solid understanding of ML concepts and experience applying them to real-world problems.
• Strategic and collaborative : You can zoom in and out between business-level vision and data-level implementation. You’re able to clearly explain complex topics to non-technical audiences.
• Autonomous and accountable : You’re able to drive initiatives forward independently and take ownership of your decisions.

Your experience:

• Master’s degree in quantitative finance, applied mathematics, statistics, or a related field.
• Minimum of 3 years experience in a credit risk or quantitative modeling role, ideally within a fintech, bank, or financial institution.

You're not sure if you meet 100% of the criteria and that's making you hesitate to apply?

At Alma, we believe that diversity drives innovation and strengthens our community and are committed to creating a workplace where everyone feels respected, valued, and empowered to contribute. We are proud to be an equal opportunity employer and welcome applicants from all backgrounds and experiences. All employment decisions are made based on qualifications, experiences, merit, and business needs without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other legally protected characteristic.

So please take your chance, apply anyway !

About the recruitment process

• Introductory call with our Talent Acquisition Manager
• Interview with the hiring manager
• Technical interview with team members
• Final interview with Head of Risk Modelling team