Data Scientist

Our mission is to be the leading platform for returned and excess inventory, connecting buyers and sellers worldwide. Through our cloud-based, multi-channel selling technology, online remarketing expertise, and full suite of business intelligence tools, we offer our clients the optimal solution for managing their reverse logistics and creating a more sustainable supply chain.

Optoro’s Data Science team is responsible for turning our massive data resources into actionable insights that inform our products and business processes. Our team values creativity, willingness to embrace new methods and technology, and the ability to solve problems independently.

• Develop statistical models via supervised and unsupervised machine learning, statistical analysis, and other predictive modeling techniques that address business challenges.
• Manipulate complex, high-volume, high-dimensionality data from varying sources to provide insights into enhancing Optoro’s SmartDisposition™ and pricing algorithms.
• Use natural language processing and related techniques to explore unstructured product content data and automate content-generation processes.
• Monitor results of deployed algorithms for accuracy, drift over time, and robustness to new data.
• Design and execute A/B and multi-armed bandit tests of new business logic.
• Communicate complex quantitative analysis in a clear, precise, and actionable manner to diverse stakeholders.
• Produce ad hoc reports and data visualizations within Tableau and other platforms.

• Strong mathematical and statistical background; B.A. (graduate degree preferred) in a relevant technical field (e.g. applied mathematics, statistics, physics, economics, computer science, operations research); or 4+ years experience in a relevant role.
• Deep understanding of data modeling, predictive analytics, and machine learning across multiple domain areas.
• Experience with the Python statistical programming stack (NumPy, pandas, scikit-learn, etc.) preferred; or experience with equivalent tools in R or other languages.
• Ability to deal with ambiguity in a fast-paced, dynamic environment.
• Proven experience thinking creatively about challenging analytical problems.
• eCommerce experience and/or domain knowledge in microeconomics preferred.
• Experience with SQL preferred