Top Senior Level Data & Analytics Jobs

As a Principal Applied Scientist, you will lead the delivery of AI products, collaborate with ML engineers, improve data quality and usability, and engage in public-facing content to enhance Xero's profile. The role requires a focus on creating impactful, customer-facing ML and AI solutions while emphasizing high-quality code from the outset.

The Senior Director of Data will lead a multidisciplinary data organization focused on analytics, data infrastructure, and AI initiatives. Responsibilities include building data strategies, managing a team of data professionals, and ensuring effective use of customer data while partnering across the organization to optimize product features.

As a Lead Data Analyst, you will direct data-driven strategies to enhance member experiences, support growth through actionable insights, and lead cross-functional data initiatives. Your role involves advanced analytics, mentoring junior analysts, and communicating complex data insights clearly to stakeholders.

The Marketing Technology Data Engineer will design and build data solutions for managing and integrating real-time and batch data, focusing on data quality and availability for enterprise clients. The role involves developing data pipelines, implementing CI/CD processes, and collaborating with teams to meet client needs while leveraging Google Cloud services.

The Sr. Manager of Credit Risk Analytics is responsible for developing credit risk strategies, leading data-driven initiatives, managing a team of risk analysts, and collaborating with cross-functional teams to optimize portfolio performance and reporting. The role involves advanced data analysis and strategic recommendations to senior leadership.

As a Senior Data Engineer, you will focus on building data infrastructure, managing ETL pipelines, collaborating with analysts, maintaining databases, and implementing process improvements. You will lead the development of data services and stay updated with cloud technologies to enhance data handling across the company.

Develop and maintain data platforms, architect data pipelines, and collaborate with stakeholders to drive operational efficiencies. Improve system performance and ensure data security and compliance. Share knowledge through documentation and mentoring.