Top Analytics Jobs in Columbus, OH

The Director, Research - Power Markets is responsible for leading the QA/QC process for long-term forecasting, advising leadership, and ensuring market insights are effectively integrated into forecasts.

Lead end-to-end architecture for a multi-year Core Banking modernization, define target and transition architectures, align business and platform strategy, govern design decisions, influence vendor/platform selections, advise senior leadership, and provide hands-on architectural guidance to delivery teams to ensure consistent, scalable migration and modern data platform adoption.

Support home lending risk strategy by performing data-driven analyses, identifying trends, monitoring emerging housing and regulatory risks, and delivering clear recommendations and visualizations. Partner with Risk Policy, Product Strategy, and cross-functional teams to design risk segmentation, controls, and performance monitoring to align growth with the firms risk appetite.

Perform end-to-end quantitative analytics for deposit pricing, focusing on CDs and elasticity testing. Analyze large money-movement datasets to inform pricing strategy, build automated interactive dashboards, ensure data accuracy, monitor competitor and macro trends, and present insights to senior leadership while partnering with pricing, finance, risk, marketing, and product teams.

Lead end-to-end quantitative research and segmentation studies using SQL, Python, and statistical methods. Analyze large datasets and surveys, synthesize findings into executive-quality insights, drive process improvements, mentor junior staff, and partner with product and senior stakeholders to integrate research into product development.

Lead analytics for branch network optimization, new branch and ATM strategy by integrating internal and external data, producing actionable insights, presenting to senior leaders, and partnering cross-functionally to champion analytics best practices.

Perform quantitative analyses of business lending portfolios to generate strategy recommendations, monitor portfolio and collection performance, design and test risk/growth strategies, produce periodic reporting, support ad hoc requests, and maintain audit‑ready documentation and controls.

Design and implement forecasting and automation solutions for finance. Translate business requirements into development-ready artifacts, collaborate with stakeholders and engineering, monitor solution performance, and document progress in JIRA.

Lead end-to-end MIS delivery including requirements, data acquisition, ELT/ETL pipeline development, validation, and dashboarding. Build automated pipelines, implement CI/CD/version control, apply advanced analytics (forecasting, anomaly detection, segmentation), enforce data quality and governance, translate insights for executives, prioritize and manage initiatives, mentor junior staff, and ensure audit-ready documentation and reproducibility.

Lead end-to-end analytical projects for alternative lending: define metrics, source and analyze data, design experiments, build reports and present insights to senior leadership to influence product and customer strategies.

Perform quantitative analyses of business lending portfolios to inform strategy across acquisition, underwriting, portfolio management, collections and recoveries. Develop reporting, test pre/post-implementation impacts, produce actionable recommendations balancing growth and credit risk, and maintain audit-ready controls and documentation.

Perform advanced fraud risk analyses, develop and implement point-of-sale fraud strategies (rules, cutoffs, policies), identify key metrics, collaborate with cross-functional partners, and present findings to senior management to reduce fraud losses while minimizing customer impact.

Lead portfolio-level product operations and change management to drive adoption of AI and analytics tools. Design and run persona-based training, measure adoption and effectiveness, coordinate cross-product priorities, and enable operational efficiency by partnering with HR, analytics teams, and stakeholders to ensure successful AI upskilling and sustained value realization.

Perform analytics across voice and digital channels to identify customer journey friction, build repeatable insights, design tests, create dashboards, and present executive-ready recommendations to improve experience and reduce operating costs.

Support development and validation of deposit forecasting and pricing models by extracting and analyzing data, translating business requirements into technical solutions, collaborating with engineering and modeling teams, performing UAT and sensitivity analyses, and delivering actionable insights to drive finance and treasury decisions.

Design, build, and operationalize analytical solutions and data pipelines for financial reporting. Create dashboards, automate reports (Alteryx/Python), enforce controls, document lineage, partner with Finance and Technology, and drive adoption and continuous improvement.

Lead definition and execution of enterprise data strategy; design and govern modern data ecosystems (lakehouse, data mesh, knowledge graphs, streaming); build reusable data products and pipelines; ensure compliance with enterprise standards and regulatory requirements; produce architectural artifacts; collaborate across teams to support analytics, reporting, and AI-driven solutions.

Help new Dynatrace customers adopt Digital Experience capabilities (Synthetic Monitoring, RUM, Session Replay). Perform data-driven analysis, create concise enablement and investigation deliverables, prioritize customer onboarding activities, drive usage expansion, and collaborate with account teams while communicating findings to technical and business stakeholders.

Perform end-to-end analytics to quantify partner value and build ROI narratives from pilot datasets. Support sales and partner success with discovery calls, fraud strategy discussions, presentations, technical support, and thought leadership (white papers). Coach team members, maintain customer relationships, and communicate insights to senior stakeholders to drive adoption.

Lead global Customer Success analytics strategy, architect data and health/adoption models, oversee data pipelines, deliver executive-level storytelling, mentor an analytics team, and drive cross-functional KPI alignment and self-serve BI adoption.

Build and maintain cloud cost monitoring, alerting, and optimization tooling. Develop automation, cost allocation/tagging, data pipelines, dashboards, and integrations with billing APIs. Support FinOps processes, implement cost guardrails, troubleshoot cost systems, participate in on-call rotation, and collaborate with senior engineers and product teams to drive cost-efficient infrastructure and reporting.

Design, build, and maintain end-to-end data models and pipelines to support CX operations, compliance reporting, and customer insights. Create dashboards and metrics, enforce data quality and governance, automate recurring workflows, and partner with stakeholders and broader data teams to deliver self-serve analytics solutions.

Build AI-augmented BI dashboards, semantic layers, and AI-ready metadata. Use AI-assisted tools to accelerate SQL and dashboard development, productionize ML outputs into BI, enforce data quality and governance, and present insights to business stakeholders including C-suite.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.

Own SQL and dbt-based data modeling and data quality for clinical and claims datasets. Author and refactor dbt models/tests, triage DQ alerts, design monitors, optimize SQL performance, and collaborate with Data Engineering and stakeholders to ensure trusted production datasets.