Staff Data Scientist, Dmarts - Quick Commerce

Job description

We are on the lookout for a Staff Data Scientist in Quick Commerce to join our team and help us take our forecast and operations to the next level. Be part of 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 Delivery Hero the go-to platform for a broad range of products, helping us grow faster and deliver more value to customers around the world.

The team's mission is to improve vendors' experience and bring value to the critical path of supply chain process through data science and data engineering. You will be working with an international and experienced team, shaping the experience for millions of customers who order daily through our platform. You’ll bring in World-Class AI and ML Expertise to help design, build, and maintain the features and ML models that behind our operations.

You'll drive engineering excellence and collaborate closely with our fellow colleagues. Join us in building and maintaining this mission-critical service! Develop, test, and productionize forecasting algorithms using state-of-the-art machine learning, statistical inference, and optimization models. Contribute to building our models for personalized recommendations. Work in cross-functional teams across disciplines such as product, engineering and design.

Own technical strategy and long-term vision for ML platform architecture; guide teams across the org on ML strategy and integration, ensuring reliability and stability Stay on top of new technologies and industry trends in data science, customer analytics, and retention strategies. Define and evangelize ML/DS best practices, standards, and frameworks across the QCommerce Operations Tribe and related domains

Qualifications

• 9+ years of experience in Data Science designing robust end-to-end data workflows, and at least
• 5 years of experience with forecasting techniques or optimization
• Proven track record building or scaling ML platforms across the full lifecycle.

Experience defining and implementing ML best practices and standards at scale Solid programming skills in Python, Docker and cloud platforms (AWS or GCP). Deep operational knowledge of AI frameworks (e.g., TensorFlow, PyTorch) and experience with LLMs Proven ability to influence and align stakeholders across organizational boundaries without direct authority Excellent written and verbal communication skills in English.

Nice to haves

Familiarity with orchestration tools (e.g., Airflow, Kubeflow, MLflow). Expertise in supply chain planning