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Join a leading marketing measurement platform as a QA Engineer specializing in Data and ML, where you'll be pivotal in ensuring data integrity and the accuracy of machine learning models. Collaborate with talented teams and take part in a fast-growing company with an impressive portfolio of clients. Enjoy competitive benefits including 25 days of holiday and flexible working arrangements.
Fospha is the marketing measurement platform for eCommerce brands. We have found product/market fit in the last two years and quickly become a market leader for measurement with numerous awards and rocket-ship growth to match. We are the only business of our type to be a certified partner of Meta, TikTok and Snap, and have worked with our customers -some of the best-known eCommerce brands in the world to drive massive growth and value. We are now expanding globally and are looking for excellent candidates to join the next phase of our journey.
The Role:
As a QA Engineer specializing in Data and ML, you'll be responsible for guaranteeing the integrity and accuracy of our product's most critical components. Your work will directly impact the effectiveness of our marketing solutions and the trust our clients place in our data. You'll be a key contributor to two primary areas:
Data Engineering QA
You'll own the quality assurance of our data pipelines. While experience with dbt (data build tool) is a plus, it's not mandatory. We do, however, require a strong understanding of SQL to verify data consistency, accuracy, and ensure product outputs remain correct across different releases and new features. We have established robust practices here, and you'll be key in helping us further refine our processes by developing and implementing even more comprehensive automated QA solutions for our data pipelines. During the initial setup and evolution phases, you'll also perform thorough manual QA to identify and address any discrepancies, helping us to strengthen our quality assurance efforts. You'll be a champion for data integrity, identifying and flagging any anomalies or regressions in our data outputs.
ML Engineering QA
You'll be responsible for rigorously testing the outputs of our machine learning models. This involves ensuring that model predictions and behaviors are accurate and align precisely with the expectations and research conducted by our Data Science team. We're looking for someone to help us enhance our existing testing frameworks for ML models, driving greater confidence in our predictive capabilities. You'll also work to validate the performance and accuracy of our ML models against defined metrics and benchmarks.
Key Responsibilities: