Data Scientist / Data Quality Lead

Are you a data scientist who wants to own data quality at scale for one of the longest-standing names in competitive pricing intelligence - at the moment it’s redefining what it delivers?

We are a market-leading competitive data business. For over two decades we’ve acquired pricing and availability data from across the web, at scale, and delivered it to some of the largest names in travel, retail, and beyond - today held in a ~2-trillion-row data lake. Our customers run real pricing and revenue decisions on our data, so as the business enters its next chapter, the quality of that data, provable and defended, is becoming the product itself.

This is a 3-month engagement to design and build our data-quality and assurance function - a define-and-build role, hands-on from day one - with a clear path to converting into the permanent role that owns it. You’ll architect the system and stand it up yourself, work on problems that matter from week one, and shape where the business is going.

What you’ll do in the first three months * Architect and begin building the observability platform - the signal framework, health scoring, and pipeline instrumentation - on top of an existing Snowflake lake and telemetry proof-of-concept.

• Define what “good” looks like across freshness, completeness, coverage, and accuracy, and build the detection that surfaces problems before customers see them.
• Answer real, open data-quality questions from several of our largest accounts - the kind their own data-science teams are asking - and use them to shape what the platform must catch.
• Trace anomalies to root cause - a source-site change, a collection failure, a processing error - and turn a monitoring blueprint into a running system.

You may be a data scientist, data-quality engineer, or data-reliability specialist who has lived close to large, messy, real-world data - and cares that it’s right. You likely have: * 5+ years in data science, data quality, or data reliability on large-scale real-world datasets.

• Strong command of anomaly detection, baselining, and statistical quality signals.
• Experience root-causing data issues across collection, processing, and source-side change.
• Fluency with SQL and Python, modern data-warehouse environments (Snowflake or similar), and observability tooling.
• Availability to start within ~2 weeks.

Especially strong if you’ve worked with competitive pricing, rate, or marketplace data, or come from a consumer-travel / OTA or rate-intelligence background.