Quantitative Credit Risk Analyst

AI overview

Drive the development of quantitative risk methodologies to enhance credit scoring, optimize risk-return balances, and collaborate across teams to improve decision-making.

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

 

At Alma, we are convinced that trade must be well balanced to be sustainable. Because finance has a key role in business, our mission is to put it back in its rightful place : at the service of merchants and consumers! That’s why we create financial products that empower merchants to sell more, and help consumers purchase better products while never encouraging them to get over-indebted. Our tech solutions are accessible to all, easy to implement, and that eliminate purchase friction. For merchants, our instalment and deferred payment solutions are excellent ways of increasing customers' loyalty and satisfaction, as well as generating up to 20% extra sales revenues without any risk. For consumers, the purchase experience is enhanced (4.8/5 on Trustpilot) and Alma helps them handle their budget easily. They pay later, Alma pays the merchants right away. We are the leader in France and are on track to win the European market on the (very) powerful Buy Now Pay Later (BNPL) industry, as we’re now processing payments in 10 European countries. Over the past 5 years, more than 16 000 merchants have chosen Alma to be their innovative BNPL solution, and we have served over 5 million consumers. The team has grown from 2 to 300+ people, we raised a €115M series C early 2022 to help us accelerate further and Alma is already part of the French Tech 120 ranking of the most promising French technology companies. And that's only the beginning.

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