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Similarweb is a leading digital intelligence platform serving over 3,500 global customers including Google, eBay, and Adidas. The company went public on the NYSE in 2021 and continues to grow rapidly.
You'll join the R&D department as a Data Analyst focused on product data quality and AI model evaluation. Your core mission is to own data quality for Similarweb's Retail Intelligence products, which use LLMs and ML models to classify, normalize, and structure product data from retailers and marketplaces worldwide into a single trusted view.
Key responsibilities include:
- Analyzing product, brand, and category data to identify gaps, errors, and opportunities for improved coverage and accuracy
- Defining quality metrics and building dashboards and automated checks to track them over time
- Building and maintaining ground-truth datasets, developing labeling guidelines, and running labeling processes
- Evaluating LLM and ML model outputs through error analysis and comparative evaluation, translating findings into concrete improvements
- Leveraging LLMs and AI tools to accelerate analysis, labeling, and data review workflows
- Collaborating with Product to define and maintain taxonomies and classification rules
- Supporting customer-facing teams with deep-dive analyses of market segments and investigating data gaps raised by clients
- Validating new data sources before product integration
- Partnering with Product and engineering to translate findings into requirements and priorities
This role is ideal for someone curious and hands-on who enjoys digging into complex data, uses AI tools to work more efficiently, and wants to see their analysis directly shape the product roadmap. You'll work closely with engineers, data scientists, and product teams in a collaborative environment.
Requirements:
- Bachelor's degree 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
- Python proficiency for data analysis (pandas, notebooks) – required
- Solid understanding of statistics and evaluation metrics (sampling, precision/recall, confidence levels)
- Hands-on experience using LLMs for data work (prompting, structured outputs, reviewing model outputs)
- Strong attention to detail and structured approach to messy, ambiguous data
- Clear English communication and ability to present findings to Product, engineering, and customer-facing teams
- Advantage: Experience with labeling, taxonomies, or data quality processes
- Advantage: Experience with e-commerce or product data
- Advantage: Experience with BI and visualization tools
The company emphasizes in-office collaboration with flexibility to work partially from home, fostering a connected and unified culture.
