The risk team mission is to enable Alma to grow quickly and securely by anticipating and preventing any risks that could endanger the company. In short, this means:

• Building tools and processes that allow us to accurately assess the risk level of our merchants during onboarding and throughout the entire relationship
• Continuously improving our customer scoring model with the objective of offering a frictionless payment experience while minimising defaults and maximising client acceptance
• Preventing and thwarting any fraud attempts from our clients or merchants

About the Job

As a Machine Learning Engineer / Data Scientist, you will join the AI/ML team (part of the Risk Modelling team). You will be responsible for developing and deploying ML models used in our real-time credit risk evaluation, which are at the core of Alma's mission to offer a frictionless payment experience while minimising defaults and maximising client acceptance.

Joining forces with the team, you will:

• Own the entire Machine Learning lifecycle, from data collection to model development and deployment in production
• Leverage ML algorithms and statistical methods to iteratively improve the performance of our credit scoring and extend its capabilities
• Collaborate closely with multiple teams to ensure the successful execution of your projects
• Understand Alma's business model and proactively identify new opportunities to leverage ML
• Follow ML research, learn new techniques, and apply them to drive business impact
• Share your knowledge and expertise with your teammates and Almakers

Over the course of your experiments and deployments, your impact on customer experience and our bottom line will be significant and easily observable.

About you

This role requires a wide skill set and a high level of energy:

• 2+ years of experience in machine learning with a master's degree (or 5+ years with a BS) in a relevant field (computer science, machine learning, mathematics, engineering, etc.)
• Solid understanding of ML fundamentals, including algorithms and concepts such as data leakage, bias-variance tradeoff, under/over-fitting, etc
• Production-level development experience in Python and SQL: unit testing, versioning (git), and documenting your code
• Advanced analytical skills, with the ability to deep-dive into a problem and quickly deliver pragmatic, tangible results, without getting lost in unnecessarily complex reasoning
• Autonomy and ownership on complex projects, capable of getting out of your comfort zone while staying focused, prioritising and communicating in a context of uncertainty
• Energetic and enthusiastic team player with clear communication skills
• Fluency in English (prerequisite, French is a plus)
• Nice to have:
  • Proficiency with cloud computing platforms (GCP preferred)
  • Hands-on experience with container-based deployments (Docker, etc.)
  • Proficiency in a deep learning framework (PyTorch or TensorFlow)
  • Experience interacting with graph databases
  • Experience in credit scoring or the BNPL ("Buy Now Pay Later") industry

ML Stack: Python, FastAPI, VertexAI, BigQuery, PostgreSQL, Github, scikit-learn, PyTorch

Recruitment process

Because of the importance of this role for Alma, the process is quite intense. Yet, we'll aim at making it as swift as possible and adapt to your contraints:

• First call with Baptiste, ML Team Lead
• Applied ML / Python interview
• ML system design interview
• Senior Almaker interview with Quentin (Head of Risk Modelling) or Guillaume (co-founder)