Top Senior Analysis Reporting Jobs in Columbus, OH

As a Product Analyst, you will analyze customer behavior and product performance, create dashboards, and support decision-making through data insights and metrics definitions, while collaborating across teams.

As a Senior Data Analyst, you will analyze marketing performance, implement multi-touch attribution, and provide insights for strategic decisions.

The Senior Data Scientist will develop and deploy analytical models supporting marketing strategies, assess campaign effectiveness, and optimize customer engagement strategies, employing advanced data-driven methods and partnering with marketing stakeholders.

Lead analytics implementations using Google Analytics and Tag Manager for clients, providing mentorship and managing projects with a focus on enhancing clients' digital strategies.

The Senior Data Engineer II will design and maintain scalable data pipelines, collaborate with teams on machine learning workflows, and ensure data accessibility across systems.

The Market Risk Analyst will monitor SBL lines of credit, assess market risks, manage collateral, develop risk models, and prepare reports.

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.

Lead Pager Health’s enterprise data and reporting strategy, build a centralized data and reporting shared services function, own internal dashboards and client-facing analytics, partner with Product and Engineering on data architecture and governance, mentor data teams, prioritize and deliver data initiatives, and drive continuous improvement in tooling, automation, and data storytelling to support growth, efficiency, and client outcomes.

Design, develop, and maintain forecasting and optimization models for contact forecasting, headcount planning, staffing and budget. Partner cross-functionally to produce data-driven recommendations, present to leadership, and mentor forecasting analysts.

Lead end-to-end data science initiatives: design, deploy, and monitor production ML models for credit risk, pricing, collections, and fraud. Partner cross-functionally to integrate models, set development standards, mentor team members, and maintain reliable, scalable machine learning pipelines and monitoring systems.