Data Scientist - Quick Commerce

Job Description

We are on the lookout for a Data Scientist to join our Quick Commerce team on our journey to always deliver amazing experiences. We are redefining how customers experience quick commerce. You’ll help build technology that scales our non-food offerings, reaching new market segments and driving revenue growth. By innovating within our Quick Commerce Team, you’ll make our organization the go-to platform for a broad range of products, helping us grow faster and deliver more value to customers around the world.

At Content & Assortment, we are building the AI engine that powers our global product catalog. We want every product to be perfectly described, categorized, and presented to our customers. Our mission is to automate and optimize the entire lifecycle of our product catalog—from creation and enrichment to categorization and curation—using advanced Machine Learning.

Your Mission

• Design, experiment, and deploy AI/ML models/Agents to automate the enrichment and moderation of product attributes at scale.
• Drive experimentation: formulate hypotheses, validate model performance, analyze business impact, and turn insights into production-ready models.
• Develop and provide ML models to intelligently curate the product assortment, including attribute extraction, product categorization, category tree recommendations, and the curation of high-impact featured categories.
• Keep yourself up to date and apply state-of-the-art models (e.g., in NLP, deep learning, classification, LLMs/AI agents) to see what truly works best for our catalog automation.
• Collaborate closely with MLEs and Engineers to ensure solutions are scalable, reliable, and fast in production.
• Contribute to the long-term vision of catalog automation and AI-driven assortment, while delivering short-term wins that unlock measurable business impact.

Qualifications

What you need to be successful:

• 3+ years of industry experience applying Data Science and Machine Learning in production, ideally in large-scale consumer-facing applications.
• Deep expertise in building and deploying ML models, particularly in Natural Language Processing (NLP), classification, recommendation systems and LLMs or agentic frameworks.
• Strong statistical foundations and ability to distinguish signal from noise in large-scale experimentation and model validation.
• Excellent engineering skills: write clean, maintainable Python code; experience bringing ML models into production with best practices for observability, monitoring, and performance.
• Experience with large-scale ML model validation, experimentation, and A/B testing.
• Proven ability to work cross-functionally with engineers and product stakeholders, translating business problems into data science solutions.

Nice to have:

• PhD in AI, Machine Learning, or a related field.
• Experience scaling catalog automation or content generation systems across multiple markets and heterogeneous platforms.
• Experience in designing or building Agentic AI systems.
• Experience in fine tuning Large Language Models.
• Familiarity with cloud platforms (GCP preferred).
• Contributions to the data science community (conference talks, papers, OSS).