Data Analyst, Product Data and AI Quality
Join the R&D team of a digital intelligence company to improve the accuracy and coverage of retail product data. Partner with product, engineering, data science, and customer-facing teams to assess data and model quality and translate findings into product improvements. The role offers partial work-
תחומי אחריות
- Analyze product, brand, and category data to identify gaps, errors, and opportunities to improve accuracy and coverage
- Define data quality metrics and build dashboards and checks to monitor them
- Build and maintain ground-truth datasets and labeling guidelines, and run labeling processes
- Evaluate LLM and machine learning model outputs through error analysis and comparisons, and recommend improvements
- Use LLMs and AI tools to accelerate analysis, labeling, and data review
- Help maintain taxonomies and classification rules with Product
- Support customer-facing teams with deep-dive analyses and investigation of client-reported data gaps
- Validate new data sources before product integration
- Translate findings into product requirements and priorities with Product and engineering
דרישות
- Bachelor’s degree in industrial engineering, statistics, economics, computer science, or another quantitative field
- At least 2 years of data analyst experience, preferably at a technology company
- Strong SQL skills
- Python experience for data analysis, including pandas and notebooks
- Understanding of statistics and evaluation metrics, including sampling, precision and recall, and confidence levels
- Hands-on experience using LLMs for data tasks, such as prompting, structured outputs, or reviewing model outputs
- Strong attention to detail and a structured approach to ambiguous data
- Clear English communication and ability to present findings to cross-functional teams
יתרון
- Experience with data labeling, taxonomies, or data quality processes
- Experience with e-commerce or product data
- Experience with BI and visualization tools
הטבות
- Competitive compensation and benefits
- Career development resources, including coaching and learning opportunities
- Regular team outings and social events