Top Senior Analysis Reporting Jobs in Omaha, NE

The Senior Manager, Performance Data Operations leads the Population Health Impact team, driving performance improvement initiatives, building complex datasets, and communicating insights to stakeholders. Responsibilities include data analytics, program management, and fostering cross-functional relationships.

The Senior Data Engineer will build and manage data pipelines in Snowflake, integrate AI systems, and ensure data security and optimization while collaborating across teams to support revenue analytics.

The Data Product Manager will oversee the firmographic data foundation, improving data accuracy, structure, and analytics capabilities to enhance talent acquisition and analytics solutions for clients.

As a Staff Data Scientist at SentiLink, you will develop fraud detection models, conduct analyses, collaborate across teams, and drive the development of financial risk products.

As a Business Analyst II, you will act as an internal consultant to improve business processes, implement scalable solutions, and ensure data governance and reporting tools are effective for stakeholders.

As the Director of Data, you will lead data engineering and analytics, develop strategies for data integration and use AI technology to drive business decisions, while managing a high-performing team.

The Senior Business Operations & Analytics leader will support executive decision-making, define metrics, and improve operational efficiency across Filmhub, partnering closely with the CEO and other leaders to enhance performance and clarity as the company scales.

As a Senior Credit Risk Manager, you'll oversee credit risk underwriting for Plaid Transfer, manage financial exposure, make risk decisions, and collaborate with multiple teams to ensure safe and scalable money movement.

Remote Operations Manager responsible for overseeing daily operations of a plumbing and heating service division. Optimize workflows between dispatch, field technicians, customer service, and project teams; implement KPIs, manage budgets and vendors, lead performance meetings, and drive continuous improvement to scale operations and improve customer satisfaction.

The role involves building and optimizing data pipelines, modeling datasets, applying machine learning techniques, and supporting data strategies. Candidates should have experience with Python, data lakes, warehousing, and related technologies.