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The role involves managing product requirements, researching customer problems, participating in agile cycles, and supporting customer onboarding and communications.

The Senior Data Scientist will build forecasting and optimization models for media inventory and campaign planning while translating business problems into actionable data science solutions. They will work with large datasets and collaborate with product and engineering teams to implement models in decision systems.

Own and drive the frontend of a data-intensive SaaS product: design React/TypeScript architecture in a Turborepo, implement typed API contracts, build interactive visualizations, enforce AI-native engineering practices and automated tests, optimise performance and accessibility, mentor engineers, and contribute to CI/CD and frontend standards.

Lead technical customer engagements for a B2B SaaS audience-measurement platform: gather requirements, design and implement data integrations, maintain ingestion pipelines (Airflow/Kubernetes), collaborate with sales, product and engineering, and act as trusted advisor to clients across Japan/Asia.

As a Data Quality Engineer, you'll ensure the accuracy of data on customer analytics platforms, identify data quality issues, create and automate test cases, and collaborate with developers to enhance product quality.