Top Data & Analytics Jobs

Support stability and success of software updates and product launches by partnering with Product and Engineering. Use dashboards and data analysis to monitor KPIs, diagnose root causes, drive escalations, validate launch readiness, enhance agent tools, and lead AI/automation initiatives to improve agent performance and customer experience.

The eCommerce Web Analyst supports teams by analyzing eCommerce data, creating dashboards, conducting A/B tests, and ensuring data accuracy to inform business strategies.

The Platform Engineer, ClickHouse administers and secures ClickHouse clusters, manages Kafka ingestion, integrates with AWS, and ensures CI/CD practices. Responsibilities include schema management, access control, and cluster health monitoring.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.

The Senior Associate in Analytics & Business Insights analyzes complex datasets to extract insights, informs commercial strategies, and collaborates with sales teams to translate data into actionable recommendations.

The Senior Data Scientist will lead analytics projects, define success metrics, run experiments, and present data-driven insights to influence product and business strategies.

The Data Scientist will analyze financial data, develop predictive models, and communicate insights to drive business initiatives in financial services. Responsibilities include mentoring junior staff and collaborating with cross-functional teams to enhance analytic products.

The Principal Data Engineer at NBCUniversal leads the development of data applications, manages data pipelines, and collaborates with teams while coaching junior engineers. Responsibilities include designing scalable data solutions and integrating AI technologies.

Lead client-facing programmatic analytics: design tests and measurement plans, monitor and report campaign performance, deliver actionable insights and optimization recommendations, and collaborate with product and engineering to improve models and measurement tools.

Own and modernize Upsides analytics data platform: migrate pipelines, reduce cost, improve governance, design reusable modeling/orchestration patterns, deliver domain-critical data products, lead cross-functional initiatives, mentor engineers, and support ML and product teams.