Similarweb

Data Analyst – Product Data & AI Quality

In short

Data Analyst role at Similarweb owning the quality of product, brand and category data behind the company's Retail Intelligence products. Requires strong SQL and Python (pandas, notebooks), statistics/evaluation metrics, and hands-on experience using LLMs for data work such as prompting and reviewing model outputs. The role involves building ground-truth datasets, evaluating LLM/ML model outputs, validating data sources, and partnering with Product, engineering and customer-facing teams; based in Tel Aviv-Yafo with a hybrid work setup, requiring 2+ years of data analyst experience.

Data Analyst – Product Data & AI Quality
Similarweb, Tel Aviv-Yafo
At Similarweb, we are revolutionizing the way businesses interact with the digital world by revealing to them everything that happens online. Our unique data and solutions empower thousands of customers globally, including industry giants like Google, eBay, and Adidas, to make game-changing decisions that drive their digital strategies.
We're looking for a Data Analyst to join our R&D department!
Why is this role so important at Similarweb?
Our Retail Intelligence products help leading brands and retailers understand how their products, brands and categories perform online. Behind them is data collected from retailers and marketplaces around the world, each describing products in its own way. We use LLMs and ML models to classify, normalize and structure that data into a single, trusted view.
As a Data Analyst on the team, you'll be the person who knows this data best. You'll own its quality: defining what "correct" looks like, building the ground truth our models are measured against, and finding where things break and why. You'll work closely with the engineers and scientists who build our LLM and ML pipelines, and with Product, turning what you find into clear priorities. Your work will also directly support our customers: partnering with our customer-facing teams on deep-dive analyses, and investigating and fixing the data gaps that matter most to clients.
It's a role for someone curious and hands-on, who enjoys digging into data, uses AI tools to move faster, and wants to see their analysis directly shape the product.
What will you be doing all day?
Your daily responsibilities may include:
•Analyzing product, brand and category data to find gaps, errors and opportunities to improve coverage and accuracy
•Defining quality metrics and building the dashboards and checks that track them over time
•Building and maintaining ground-truth datasets and labeling guidelines, and running labeling processes
•Evaluating the output of LLM and ML models: error analysis, comparing approaches, and turning findings into concrete improvements
•Using LLMs and AI tools to speed up analysis, labeling and data review
•Helping define and maintain taxonomies and classification rules together with Product
•Supporting client-related needs with our customer-facing teams, from in-depth analyses of specific market segments to investigating and fixing data gaps raised by clients
•Validating new data sources before they are added to the product
•Partnering with Product and engineering to translate findings into requirements and priorities
This is the perfect job for someone who:
•Holds a B.Sc. in Industrial Engineering, Statistics, Economics, Computer Science or another quantitative field
•Has 2+ years of experience as a data analyst, preferably in a tech company
•Has strong SQL skills
•Uses Python for data analysis (pandas, notebooks) - Must
•Has a solid understanding of statistics and evaluation metrics: sampling, precision/recall, confidence levels
•Has hands-on experience using LLMs for data work, such as prompting, structured outputs or reviewing model outputs
•Has strong attention to detail and a structured approach to messy, ambiguous data
•Communicates clearly in English and can present findings to Product, engineering and customer-facing teams
•Has experience with labeling, taxonomies or data quality processes (advantage)
•Has experience with e-commerce or product data (advantage)
•Has experience with BI and visualization tools (advantage)
At Similarweb, collaborating with our colleagues in-office creates a more connected, unified culture. Our best work is a product of our face-to-face collaboration, with the ability to work partially from home.

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