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Similarweb is a public digital intelligence platform (NYSE-listed since 2021) that helps thousands of global customers—including Google, eBay, and Adidas—understand online behavior and make data-driven digital decisions.
You'll join the R&D department as a Data Analyst focused on Product Data & AI Quality. The role centers on ensuring the integrity and accuracy of Similarweb's Retail Intelligence products, which aggregate product, brand, and category data from retailers and marketplaces worldwide. Behind these products are LLMs and ML models that classify, normalize, and structure diverse data sources into a single trusted view.
As the data expert on the team, you will own data quality by defining correctness standards, building ground-truth datasets that models are measured against, and identifying where and why things break. You'll partner closely with engineers and data scientists building LLM and ML pipelines, collaborate with Product to translate findings into priorities, and support customer-facing teams on deep-dive analyses and client-specific data investigations.
Day-to-day 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, labeling guidelines, and running labeling processes
- Evaluating LLM and ML model outputs through error analysis, comparative evaluation, and translating findings into concrete improvements
- Leveraging LLMs and AI tools to accelerate analysis, labeling, and data review
- Defining and maintaining taxonomies and classification rules with Product
- Supporting customer-facing teams with in-depth market segment analyses and investigating/fixing data gaps raised by clients
- Validating new data sources before product integration
- Translating findings into product requirements and priorities alongside Product and engineering
The role is hands-on and curiosity-driven, ideal for someone who enjoys digging into messy data, uses AI tools to move faster, and wants to see their analysis directly shape the product.
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
- Python 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
- Advantageous: experience with labeling, taxonomies, or data quality processes; e-commerce or product data background; BI and visualization tools
