Top Senior Analytics Jobs in Columbus, OH

Owns deposit product performance reporting and ad hoc analysis using SQL, Python, dashboards, and cloud data platforms. Translates business needs into analytical deliverables, monitors KPIs and KRIs, identifies trends and risks, automates reporting, troubleshoots production environments, and communicates actionable recommendations to senior stakeholders.

Leads a marketing analytics team that evaluates campaign performance, develops statistical models and experiments, delivers in-flight and post-campaign insights, and advises stakeholders on optimization strategies. Manages analytics initiatives, resources, data-driven research, and talent development while identifying improvements to data systems and business processes. The role requires translating complex findings into actionable recommendations and overseeing analysis of large structured and unstructured datasets.

Lead digital analytics efforts to define OKRs, run A/B tests, analyze digital customer behavior, and deliver actionable insights to product, tech, and design partners to improve engagement and customer satisfaction.

Analyze large datasets to identify digital fraud trends, develop loss-reduction strategies and business rules, automate fraud alert processes, monitor emerging risks, and present actionable insights to senior leadership. Collaborate with technical and business teams on fraud-fighting products, apply experimentation and machine learning, manage financial impacts, and improve customer experience across digital payment channels.

Manage point-of-sale fraud strategies and conduct complex risk analyses to reduce losses while balancing customer impact. Responsibilities include developing fraud rules and policies, identifying risk indicators, enhancing reporting, testing mitigation processes, leading strategy initiatives end-to-end, analyzing large datasets, and presenting recommendations to management. The role collaborates with Operations, IT, Risk Management, and other cross-functional partners to improve fraud detection and customer experience.

Partner with product, engineering, BI, and business stakeholders to define requirements, own epics/stories, validate data, enable dashboards, document data assets, manage backlog, and drive adoption of curated finance data products and analytics.

Designs and delivers data-driven audience, targeting, and measurement solutions for digital marketing campaigns. Translates business goals into technical requirements, improves data quality and reporting, standardizes audience documentation, and manages initiative execution, monitoring, issue triage, and alerts. Partners with Marketing, Product, and Technology on platform enhancements while identifying responsible artificial intelligence applications with human oversight, governance, explainability, and measurable outcomes.

Lead quantitative analytics initiatives by integrating and preparing diverse customer, financial, digital, account, and operational datasets. Analyze customer journeys, identify friction points, optimize collections features, develop KPIs, and apply statistical, machine learning, and predictive modeling techniques. Translate strategic objectives into analytics solutions, collaborate with product and technology teams, and present actionable insights to business and executive stakeholders.

Lead revenue analytics by developing business cases, dashboards, KPI frameworks, experiments, and automated analytics solutions. Partner with client success, marketplace, merchants, and cross-functional teams to evaluate performance, guide go-to-market decisions, quantify product value, and scale data-driven execution. Serve as the analytics subject matter expert while translating structured and unstructured data into actionable recommendations and compelling stakeholder narratives.

Lead end-to-end analytics for major platform partnerships, identifying growth opportunities and informing product, investment, risk, and pricing decisions. Conduct complex analyses, design experiments, build scalable data models, metrics, dashboards, and AI-assisted workflows, and translate findings into business recommendations. Partner cross-functionally with Product, Engineering, Finance, Revenue, and Strategic Partnerships while mentoring analysts and improving analytical practices.

Lead data management for marketing execution: design targeting and measurement strategies, build repeatable datasets, automate reporting, implement monitoring and quality checks, enable responsible AI-supported workflows, and quantify value from automation and audience improvements.

Lead a quant analytics team supporting AML/KYC controls by defining analytics strategy, delivering advanced data solutions, integrating AI, partnering with senior stakeholders, and improving governance and processes to drive measurable business outcomes and strengthen risk/compliance controls.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

Lead analytics and machine-learning efforts to prevent point-of-sale fraud: analyze large datasets, design and implement fraud decisioning capabilities, partner with risk modeling and cross-functional teams, build KPI monitoring and automation, and communicate findings and project outcomes to senior leadership.

Lead executive and regulatory reporting by synthesizing data from multiple systems, analyzing complaints and business trends, and translating findings into actionable insights. Build trusted analytics products, oversee reporting controls and documentation, support ad hoc analyses, and drive process improvement and automation. Collaborate with partners to identify complaint root causes, manage data changes, and present insights to senior leaders and regulators.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

Lead strategic deposit pricing analytics focused on CDs, elasticity testing, deposit trends, yield-seeking behavior, and macroeconomic impacts. Serve as the subject-matter expert on CD data, translate findings into executive presentations, build automated self-service dashboards, and partner with finance, pricing, marketing, risk, product, and branch teams. Monitor competitor pricing and economic trends to inform retail banking product decisions.

Own GTM performance analytics, KPI and target setting, reporting, forecasting, compensation planning, and performance reviews across Sales and Post-Sales. Identify anomalies and optimization opportunities involving conversion, churn, productivity, pricing, packaging, segmentation, channel economics, and customer quality. Partner with Finance and GTM leaders to develop recommendations, lead strategic initiatives, and ensure data integrity while translating analysis into actionable business decisions.

Lead a GTM Analytics team supporting Marketing, Sales, RevOps, and Customer Operations. Manage embedded analysts, establish trusted reporting and QA processes, review SQL and dashboards, guide funnel, campaign, sales, support, forecasting, segmentation, attribution, and experimentation analysis, and deliver executive recommendations. Partner with GTM leaders and data engineers, coach analysts, and develop self-service analytics, automation, governed dashboards, metric documentation, and AI-assisted workflows.

Manage and improve the Data Privacy control environment for the Chief Data Office. Identify, assess, document, and remediate data privacy risks and controls, partner with business and control stakeholders, maintain controls in CORE, drive governance, reporting, and best-practice sharing across lines of business.

Leads a team of five experienced analysts and data scientists while personally owning strategic analytics across ecommerce, health, supply chain, inventory, fulfillment, and merchandising. Partners with executives, establishes KPI and reporting standards, prioritizes the analytics roadmap, and delivers actionable business insights. The role also advances AI-native, self-service analytics capabilities, strengthens data governance and quality, and builds a high-performing analytics culture.

Lead the architecture and migration of Rula’s data platform to Snowflake and Medallion architectures. Govern warehouse performance and cloud costs, establish data contracts and intake guardrails, and enforce GitHub-based CI/CD testing for data quality and query performance. Scale AI-assisted engineering practices across teams while partnering with executives and domain engineers. The role also supports secure clinical data handling, schema evolution, semantic BI integrations, and production ELT pipeline development.

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 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.