Marketplace Quality Data Scientist
2 months ago
Faire is a leading e-commerce platform that leverages machine learning and data insights to revolutionize the wholesale industry. Our team of data scientists and machine learning engineers specialize in developing algorithmic solutions for notification and recommender systems, advertising attribution, and LTV predictions. Our goal is to empower local retail businesses with the tools they need to succeed.
As the Marketplace Quality lead within the Brand Data Science team, you will be responsible for improving the quality of retailers' experiences with products and brands on Faire. This involves reducing egregious issues, such as counterfeit products, fulfillment delays, damaged and missing items, and poor quality products. You will develop data science models to detect and act on these issues, using techniques such as issue detection from unstructured data, human-in-the-loop targeting, causal inference, and lever optimization.
Our team already includes experienced Data Scientists from top tech companies. Faire is committed to being a top destination for data scientists and machine learning engineers, and you will play a key role in helping us achieve this goal.
Key Responsibilities- Drive data science vision, strategy, and execution on Marketplace Quality, reducing the bad experiences that retailers encounter in the marketplace.
- Act as a lead on the cross-functional Marketplace Quality pod, thinking end-to-end about brand and retailer experiences, ops processes, policy enforcement, etc.
- Use deep learning techniques to match products across platforms, detect issues from image and text data, and summarize reviews.
- Use causal inference methods to estimate the long-term effects of quality issues and optimize the tradeoff between reducing issues and near-term growth.
- Optimize levers such as downranking and Top Shop status to drive visibility away from low-quality and toward high-quality products and brands.
- Develop human-in-the-loop machine learning systems for detecting issues and targeting actions.
- Solve challenging problems related to a two-sided marketplace.
- 5+ years of industry experience using machine learning to solve real-world problems.
- Experience with relevant business problems (e-commerce, marketplaces, or logistics).
- Experience with relevant technical methods (human-in-the-loop machine learning, causal inference, and/or deep learning).
- Strong programming skills.
- An excitement and willingness to learn new tools and techniques.
- The ability to contribute to team strategy and to lead model development without supervision.
- Strong communication skills and the ability to work in a highly cross-functional team.
- Highly recommended: Master's or PhD in Computer Science, Statistics, or related STEM fields.
- Previous experience in marketplace quality in a two-sided e-commerce platform.
- Previous experience in deep learning or language models.
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