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Own technical relationships with enterprise accounts across Japan and APAC, lead discovery and innovation workshops, demonstrate the analytics platform, and translate customer needs into product and engineering requirements. Build AI-powered workflows for data integration, quality checking, anomaly detection, and insight generation using cloud and data pipeline technologies. Contribute customer insights to product strategy, support sales efforts, and collaborate with distributed engineering and product teams.

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.

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.

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.

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.