Zoro.com is looking for a Lead Data Scientist to focus on customer-facing search and recommendation products and the content enrichment that powers them, applying advanced data science methodologies to address business needs and drive innovation in the B2B eCommerce space.
Requirements
- Proficiency in writing production-level Python code, developing algorithms, and deploying data science models.
- Deep expertise in statistical methods and machine learning concepts, with the ability to mentor team members on methodologies, model tuning, and evaluation techniques.
- Experience building and maintaining models for real-time applications
- Background in e-commerce, with familiarity in website metrics, search and recommendation systems, customer purchasing behavior, and marketing strategies
Responsibilities
- You serve as a technical expert, applying advanced data science methodologies to address business needs.
- You take ownership of developing and implementing new data science models within your area of responsibility, ensuring robust, effective approaches are used.
- You assess and manage risks associated with production models, making informed recommendations on model retraining, versioning, and improvements.
- You provide guidance and mentorship to team members, supporting their successful project completion.
- You advocate for and encourage the adoption of team conventions and industry best practices to maintain high standards.
- You collaborate with business partners to scope, prioritize, and initiate data science projects.
- You collaborate with other technologists to design effective solutions.
Other
- Bachelor’s degree in a technical field (e.g., Computer Science, Mathematics, Statistics, Physics, or Engineering); an advanced degree is preferred.
- 5+ years of experience in data science or a closely related discipline.
- Proven ability to collaborate with business partners, establish trust, manage timelines, and provide insightful recommendations
- Hybrid work model gives you space to focus and the flexibility to live your life — asking team members to be onsite at least two days a week.
