Data Analyst: Offsite Search Optimisation
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About the role
Constructor is the next-generation platform for search and discovery in ecommerce, built to explicitly optimize for metrics like revenue, conversion rate, and profit. Our search engine is entirely invented in-house utilizing transformers and generative LLMs, and we use its core and personalization capabilities to power everything from search itself to recommendations to shopping agents. Engineering is by far our largest department, and we've built our proprietary engine to be the best on the market, having never lost an A/B test to a competitive technology. We're passionate about maintaining this and work on the bleeding edge of AI to do so. Out of necessity, our engine is built for extreme scale and powers over 1 billion queries every day across 150 languages and roughly 100 countries. It is used by some of the biggest ecommerce companies in the world like Sephora, Under Armour, and Petco. We're a passionate team who love solving problems and want to make our customers' and coworkers' lives better. We value empathy, openness, curiosity, continuous improvement, and are excited by metrics that matter. We believe that empowering everyone in a company to do what they do best can lead to great things. Constructor is a U.S. based company that has been in the market since 2019. It was founded by Eli Finkelshteyn and Dan McCormick who still lead the company today. As a Data Analyst on the Offsite Search Optimization team you will improve the e-commerce experience for hundreds of millions of users across the world by making it faster and more personalized. The team's mission is to bridge the gap between onsite product discovery and external discovery platforms, ensuring that Constructor-powered websites can be found, understood, and correctly represented by both Google and Generative engines. The team goal is: Build measurable foundations to track visibility, traffic sources, and performance across SEO and GEO. Build the architecture to run technical checkups on customer websites, assess their optimisation level, and provide clear recommendations on what needs to be fixed. Partner with Product teams to adapt enriched content for SEO/GEO and package it toward external discoverability needs. Define an SEO/GEO enablement layer with tools, playbooks, and frameworks to scale best practices across teams and customers. Challenges you will tackle Complete visibility of the product discovery from external sources. Accurate measurement of organic, branded, AI-driven traffic. Create a unified model of landing pages. A framework for future SEO experiments (canonical tests, template variations, structured data tests). Internal tools that other teams can plug into. Run the adoption process of best practices to other teams
Requirements
- Strong SQL and Python (requests, pandas, numpy, etc)
- Experience building data integrations between products
- Experience with APIs & auth (OAuth2, GA4 and Google Search Analytics API)
- Understanding of ETL/ELT workflows on PySpark
- Building logic of data extraction from non-structured data (referrers, canonical URLs, page types)
- Experience with BigQuery or similar
- JS execution basics (how SSR/CSR affects crawlers)
- Knowledge of SEO fundamentals
- Experience with BI systems (Looker/Metabase/Superset)
- Experience with logs or event handling systems
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