Data Scientist I

Position Description:

As a Data Scientist at Zoro, you’ll apply your expertise in machine learning, statistical modeling, and data analysis to solve a variety of business challenges. From forecasting and customer segmentation to improving onsite search and recommendations, our team directly enhances our customers' experiences and informs critical business decisions. At Zoro, every day brings new challenges and opportunities to innovate.

Duties and Responsibilities: 

• Build, validate, and deploy predictive and inference models using Python to support key business initiatives.
• Review relevant academic research and collaborate with other data scientists to identify and implement suitable algorithms.
• Partner with stakeholders to understand business objectives, gather requirements and design tailored data solutions.
• Write and maintain high-quality code, including unit and integration tests.
• Debug production issues and update existing processes to meet evolving needs.
• Write clear documentation for transparency and maintainability.
• Communicate findings to business leaders and colleagues using visualizations, presentations, and reports.

Minimum Qualifications:

• Bachelor’s degree in a technical field (e.g., Data Science, Computer Science, Mathematics, Statistics, Physics, or Engineering).
• 2+ years of experience in applied data analytics/data science or a master's degree in a relevant field.
• 2+ years of experience utilizing Python for data exploration, visualization and predictive modeling.
• Demonstrated proficiency in SQL.
• Strong knowledge of statistical methods, hypothesis testing and regression analysis.
• Experience with deep learning frameworks, NLP and data mining techniques.
• Strong communication skills. Must be able to interact cross-functionally and engage in both business and technical discussions.

Preferred Qualifications:

• Experience using data science in an internet retailer or a top-tier consumer-focused company.
• Experience with deep learning frameworks, LLMs, fine-tuning, and evaluation tasks for LLMs.
• Domain knowledge and experience building models for recommendation or search systems.
• Experience using containerization tools like Docker and Kubernetes in production environments.
• Experience using orchestration tools such as Airflow or Kubeflow for production workloads.
• Experience with cloud-hosted data platforms (AWS, Google Cloud Platform, etc.)
• Knowledge of web tracking technology and web analytics tools (Google Analytics, Adobe Analytics, etc.).