Data Scientist Recommerce

How do you make our customers happy?

By developing systems that transform product returns from an inevitable cost into a value driver. Every day, thousands of products are returned to our six warehouses, creating a complex puzzle. Which items can be resold? Which should be returned to suppliers or partners? And which require alternative handling? As Data Scientist Recommerce, you’ll build predictive models that automate these decisions, reducing processing time and maximizing value recovery. Your algorithms will impact both customer satisfaction through faster refunds and business performance through optimized inventory flows.

The biggest challenge

Building accurate predictive models in an environment where product condition assessment has traditionally relied on human judgment. How do you train algorithms to evaluate and grade millions of individual products, ranging from perishable consumables to fridges to store them in? How do you balance automation speed with accuracy when every wrong classification impacts both customer trust and financial performance? Success requires translating warehouse operators’ domain expertise into scalable machine-learning solutions while maintaining the flexibility to adapt as return patterns evolve.

What you'll do as Data Scientist Recommerce

As part of the Return Solutions product group within Warehousing, you’ll lead the development of predictive models that revolutionize how we handle returns. Working with logistics engineers, product managers, and warehouse operators, you’ll transform manual processes into a data-driven and automated approach. Your models will predict product grades, optimize routing decisions, and accelerate the entire returns workflow.

You’ll dive deep into unstructured data from multiple sources. Through advanced machine learning techniques, you’ll develop algorithms that can classify product conditions with increasing accuracy over time. Your work directly supports operators who process returns, giving them intelligent recommendations to enhance their speed and accuracy. A unique aspect of this role is that you’ll help establish and improve bol’s warehousing data science community. You’ll collaborate with fellow data scientists across logistics, share methodologies, and develop best practices that elevate our analytical capabilities. This means balancing hands-on model development with knowledge sharing and community building.

Key responsibilities:

• Develop and deploy ML models for automated product condition assessment
• Design predictive systems that optimize return processing workflows
• Collaborate with engineers to translate domain knowledge into algorithms
• Team up with warehouse operators to validate and optimize model performance
• Lead initiatives to establish data science best practices across warehousing
• Present insights to stakeholders across product and operations teams
• Determine model impact on our operational metrics

Why you can make a difference

You combine 5+ years of data science experience with a passion for solving complex practical challenges. Your background in applied machine learning and unstructured data helps you tackle the challenges of product condition assessment. Experience with A/B testing and proficiency in Python, SQL, and BigQuery are must-haves. If you also have cloud platform and Google AI Platform experience, even better. Beyond tech, you excel at translating business problems into data science solutions and can communicate deep insights to diverse stakeholders. Your collaborative approach helps bridge the gap between technical possibilities and operational realities. You thrive in a setting where sharing isn’t an abstract ambition but an integral part of the job.

This role is not for you if:

• POC perfectionist – Your attention span drops dramatically after a successful proof of concept; you prefer the thrill of discovery to the discipline of deployment
• Single-solution specialist – Neural networks are your answer to every problem, regardless of complexity or data availability
• Isolated analyst – You prefer working solo to collaborating with operational teams

This role is for you if:

• Operational impact driver – You're energized by building models that directly improve real-world processes and are eager to make your mark on warehouse efficiency
• Cross-functional collaborator – You like teaming up with logistics engineers, product managers, and operators – the better you understand the domain, the better your solutions will be
• Community builder – You're excited about establishing data science best practices and sharing knowledge across the broader warehousing organization

Where you'll work

You’ll join the Return Solutions team within Core Warehousing, working alongside colleagues who share your passion for operational excellence. As part of the broader warehousing community, you’ll collaborate with professionals across six facilities that process millions of products annually. The environment combines technical rigor with the drive to make a measurable impact – we value both algorithmic sophistication and operational effectiveness. With 2,900 colleagues supporting 13.7 million customers and 47,000 partners, you’ll work on challenges at scale. You’ll have the freedom to explore innovative approaches while ensuring solutions integrate seamlessly into operations. Ready to transform returns processing? Let’s unlock the hidden insights in your experience! 🚀