Maya
Overview: We are looking for a Senior Data Scientist to build, scale, and optimize the core machine learning and data solutions powering Maya's marketing and personalization platforms. In this role, you will operate as a high-impact technical builder who bridges complex business requirements directly into robust, production-grade ML solutions. Your primary focus will be engineering and technical excellence: designing sophisticated models mainly around but not limited to, propensity, recommendation, optimization and clustering models, building scalable and cost-optimized data pipelines, writing production-grade code, and taking deep technical ownership of model validation, code quality, and automated deployment cycles. What You Will Do Translating Business Logic to Advanced ML: Analyze marketing and growth objectives to independently architect, train, validate, and deploy high-performing machine learning solutions (including supervised, semi-supervised and supervised models). End-to-End Technical Ownership & Pipeline Architecture: Build scalable, cost-optimized data pipelines processing structured and unstructured data. Handle data modeling, schema design, pipeline materialization, scheduling, wiring new data sources, and backfilling. Rigorous Model Validation & Business Physics Alignment: Execute deep technical validation to ensure model logic adheres to real-world operational constraints, handling edge cases, preventing data drift, and maintaining internal governance checks. Software Engineering & Code Quality: Write clean, modular, and performant code adhering to software engineering best practices. Does peer code reviews, refactor legacy code, and manage technical debt by systematically removing unused pipelines. What we are looking for: Bachelor’s or advanced degree in a quantitative discipline (Computer Science, Statistics, Mathematics, Data Science, Physics, Industrial Engineering, or a related field). Minimum 4–6 years of hands-on data science and engineering experience, with strong exposure to marketing analytics, CRM data, or customer lifecycle systems. Demonstrated capability to write production Python/SQL code, build and debug data pipelines, execute rigorous data quality/validation checks, and independently deploy models into production environments.
Maya
