Role Overview
The Data Analyst will be responsible for analyzing product, brand, and category data to find gaps, errors, and opportunities to improve coverage and accuracy. They will work closely with engineers and scientists to build and maintain ground-truth datasets and labeling guidelines, and run labeling processes. The Data Analyst will also evaluate the output of LLM and ML models, compare approaches, and turn findings into concrete improvements.
What You Will Do
The Data Analyst’s daily responsibilities will include analyzing product data, defining quality metrics, building dashboards and checks, evaluating model output, using LLMs and AI tools to speed up analysis, and partnering with Product and engineering to translate findings into requirements and priorities.
Why It Might Be a Fit
The ideal candidate will have strong SQL skills, experience with Python for data analysis, and a solid understanding of statistics and evaluation metrics. They will also have hands-on experience using LLMs for data work, strong attention to detail, and the ability to communicate clearly in English.
Requirements
- B.Sc. in Industrial Engineering, Statistics, Economics, Computer Science or another quantitative field
- 2+ years of experience as a data analyst, preferably in a tech company
- Strong SQL skills
- Experience with Python for data analysis (pandas, notebooks)
- Solid understanding of statistics and evaluation metrics: sampling, precision/recall, confidence levels
- Hands-on experience using LLMs for data work, such as prompting, structured outputs or reviewing model outputs
- Strong attention to detail and a structured approach to messy, ambiguous data
- Ability to communicate clearly in English and present findings to Product, engineering and customer-facing teams
Benefits
- Competitive compensation package
- Regular team outings and happy hours
- Career development opportunities
- Diversity and inclusion initiatives
To apply for this job please visit job-boards.greenhouse.io.
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