Top Senior Data & Analytics Jobs in Columbus, OH

The Product Analyst will measure results and deliver insights on new AI products, identify opportunities, and guide product strategy through data analysis and visualization.

The Sr. Data Engineer will design and maintain databases, develop ETL pipelines, and ensure data integrity for Hologram's IoT network, enabling insights and decision-making.

This role involves leading workforce analytics initiatives, delivering insights on headcount, compensation, and workforce planning, while utilizing AI tools and visual analytics platforms to support decision-making processes across various HR functions.

As Manager of Business Intelligence, you'll lead a team to shape performance metrics, develop analytical tools, engage with stakeholders, and drive BI practices across the Operations organization.

The position involves leading database operations and managing data integration for business intelligence, focusing on PostgreSQL and ETL/ELT pipelines.

The Staff Data Engineer will design data architecture, develop scalable data pipelines, ensure data quality, and lead governance practices while collaborating across teams.

As a Senior Data Scientist, analyze healthcare data to improve health outcomes, develop reports and dashboards, and collaborate across teams to leverage genomic data for health insights.

The Senior Director of Data Management leads data management strategy for clinical programs, overseeing CRO partnerships, data lifecycle management, and compliance with regulatory standards. They mentor staff and ensure high-quality clinical data for submissions.

The Senior Data Engineer will design and maintain scalable data pipelines, lead medium-sized platform projects, and ensure reliability of data systems through monitoring and optimization. Responsibilities include working with cross-functional teams to improve data workflows and participate in incident response.

The Senior Manager in R&D Data Literacy & Monetization drives the strategic utilization of R&D data, transforms datasets into reusable products, and promotes data literacy across the organization, ensuring effective governance and promoting advanced analytics and AI initiatives.