Top Data & Analytics Jobs in Cleveland, OH

The Vice President of Account Services leads analytics strategy, provides data-driven insights to clients, oversees complex analyses, and develops KPI frameworks to improve nonprofit fundraising performance, while mentoring teams and collaborating across functions.

The Data Engineer I will manage data warehouses, extend data pipelines, write SQL and Python scripts, and support data operations.

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.

The Financial Analyst will apply financial analysis and AI-driven insights to support a dental practice management software platform, focusing on subscription revenue, forecasting, and operational performance.

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.

The Senior Financial Analyst supports financial planning and analysis, conducts financial forecasting, builds financial models, and reports on financial performance to drive business growth.

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.