Data Scientist

This Data Scientist role develops data models and statistical algorithms to analyze petabytes of data from various sources, turning raw data into usable metrics and deploying ML models into production. Requires an M.Sc. in a quantitative field, 3+ years of statistical and ML experience with Python or R, and experience with Big Data tools like PySpark and AWS.

This role applies data science techniques to analyze payment data and drive business insights. The specialist builds predictive models, conducts statistical analyses, and collaborates with product and engineering teams to optimize payment performance.

This Data Scientist II role focuses on building and deploying classical machine learning models for real-world business problems such as demand forecasting, customer segmentation, and pricing. The scientist will work with large datasets, perform feature engineering, and ensure model interpretability and monitoring. Strong proficiency in Python, SQL, and cloud data platforms is required, along with experience in model productionization.

This Data Scientist role focuses on developing and deploying machine learning models for retail AI solutions, optimizing in-store operations and automating processes. The role involves working with large datasets, building predictive models, and collaborating with engineering teams to integrate AI into production systems. Key challenges include improving model accuracy and handling real-world retail data variability.

This Full Stack Developer role focuses on developing and maintaining the core Lebesgue product, collaborating with the Data Science team to build analytics-driven features. The developer will work on both frontend and backend, contributing to a scalable and user-friendly application using Python, FastAPI, React, Next.js, and AWS.

Elevate user experience and UI quality for the analytics-driven SaaS product. The role involves building and refining user interfaces, integrating APIs, and contributing to the design system. Requires strong proficiency in JavaScript/TypeScript, React, and modern frontend frameworks.

Strengthen the engineering team by scaling the analytics engine and core product. The role focuses on backend development, optimizing database performance, and ensuring system reliability. Requires proficiency in Python, FastAPI, SQL, Docker, and AWS.