Data Scientist Anomaly Detection & Product Scoring at Mirakl - Labs

Mirakl is seeking a Data Scientist to join their Data Science team. The Data Scientist will be responsible for prototyping, iterating, and deploying algorithms in collaboration with Product, Data Engineers, and development teams. The role focuses on leveraging data to improve clients' revenue, optimize marketplace operations, and ensure user and transaction security.

Mirakl Labs teams are primarily located in Paris and Bordeaux. They operate in agile mode, organized into Squads composed of a Squad Lead, 5 developers, a Product Manager, and a QA. Each Squad specializes in a functional scope to design and implement new features, their evolutions, and APIs (with a micro-services breakdown).

The Data Core team develops algorithms to enhance the quality and performance of Mirakl marketplaces.

Role Involves:

• Analyzing and preparing data.
• Prototyping algorithms.
• Deploying algorithms in collaboration with Data Engineers and development teams.
• Creating dashboards to illustrate algorithm relevance and monitor production.
• Presenting results at weekly data science meetings.
• Participating in team brainstorming sessions.
• Communicating with other teams to refine use cases, user experience, and integration methods.

Requirements:

• Background in machine learning, mathematics, or computer science.
• 2+ years of experience in a similar role.
• Experience deploying Machine Learning algorithms.
• Knowledge of Machine Learning and Deep Learning algorithms (especially State-Of-the-Art architectures like Transformers).
• Proficiency in Python, Tensorflow, or PyTorch.
• Pragmatic, data-driven, and business-oriented with good teamwork skills.
• Ownership mentality and curiosity.
• Positive attitude with respect and consideration as core values.

What This Role Offers:

• Implement algorithms with a visible impact on 500+ e-commerce sites/marketplaces in 40 countries.
• Exposure to diverse techniques (Time Series, Heuristics, Deep Learning, NLP, LLM, etc.).
• Autonomy and responsibility in owned projects.