Top Senior Analytics Jobs in Columbus, OH

Leads financial and marketing analytics across campaign planning, experimentation, measurement, reporting, and optimization. Owns stakeholder relationships, develops incrementality and ROI frameworks, applies predictive models, defines data requirements, enhances analytical tools and controls, and coaches junior analysts. Partners with marketing, finance, modeling, data, and execution teams to translate complex quantitative insights into actionable investment and growth decisions.

Leads marketing analytics across campaign planning, financial modeling, experimentation, execution support, performance measurement, and ROI optimization. Partners with Marketing, Finance, Modeling, and Data & Analytics teams to develop predictive insights, measurement frameworks, dashboards, and data requirements. Uses analytical tools and platforms to evaluate incrementality, profitability, and campaign effectiveness while maintaining repeatable, auditable processes and communicating findings to senior stakeholders.

Own deposit product performance reporting and ad hoc analysis, building SQL queries, dashboards, KPIs, and risk indicators. Partner with stakeholders to identify trends, risks, and growth opportunities; automate reporting; troubleshoot production environments; and deliver actionable recommendations. The role requires advanced SQL and Python, cloud data platform experience, Tableau, generative AI, strong communication, and stakeholder management.

Own the analytics lifecycle from complex raw data through executive-ready insights. Design experiments, analyze performance drivers, build scalable data pipelines and analytical frameworks, and communicate findings to marketing, product, and technology stakeholders. The role supports customer acquisition, owned media optimization, repeatable reporting, and roadmap decisions through secure, maintainable SQL and Python or R solutions.

Establishes and improves data governance controls, risk assessments, and control documentation across the firm. Partners with Chief Data Office stakeholders, lines of business, control teams, and leadership to identify risks, remediate gaps, maintain regulatory alignment, and improve data quality, governance, reporting, and control consistency. Serves as a subject matter expert on data governance policies, standards, processes, and controls within the CORE platform.

Designs and maintains governed, analytically ready datasets for AML/KYC operations. Builds scalable ETL and transformation processes using SQL and Python, develops metadata and semantic layers for AI and self-service analytics, and implements data quality, reconciliation, and validation frameworks. Partners with operations, data, technology, and AI teams while supporting production data assets, documenting findings, addressing source-system impacts, and ensuring compliance with controls, privacy, and regulatory standards.

Build and maintain dbt data models, SQL transformations, ingestion pipelines, orchestration, and Tableau dashboards in support of HR and enterprise analytics. Own data quality, metric standardization, privacy controls, Row-Level Security, documentation, CI/CD, and troubleshooting from source systems through reporting. Partner with stakeholders to define requirements and KPIs, support workforce forecasting, optimize BigQuery performance, and pilot AI-assisted analytics using Google Gemini.

Own marketing measurement from initial engagement through closed-won revenue. Manage cross-channel reporting tied to Salesforce pipeline, tracking across GA4, advertising platforms, SEO, and AI search. Validate multi-touch attribution, analyze marketing experiments, model budget impact, and recommend investment priorities. Present performance insights to marketing and sales leadership across global regions.

Own Toast’s Voice of the Customer program across customer segments, analyzing NPS, CSAT, CES, qualitative feedback, and business metrics. Identify root causes of customer pain, develop data-driven recommendations, improve CX measurement practices, and influence cross-functional teams to prioritize customer-focused solutions. The role also builds listening channels, promotes customer-centric decision-making, and aligns CX priorities with organizational goals.

Build Deepgram’s governed decision layer above warehouse gold tables. Responsibilities include modeling cross-system entities, owning semantic and metrics definitions, creating agent-facing data tools and MCP surfaces, implementing data quality assertions and reconciliation checks, evaluating AI agent accuracy, and answering business questions while leaving reusable models behind. The role requires production-grade SQL and Python, semantic-layer ownership, strong data modeling judgment, AI-native workflows, clear writing, and comfort building infrastructure from scratch.

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.

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.

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.

Support digital product analytics for an application status platform by defining measurement strategies, KPIs, analytical frameworks, dashboards, governed datasets, and anomaly alerts. Analyze platform data, identify trends and performance issues, communicate recommendations to product and technology stakeholders, and collaborate on instrumentation and pipelines. Use AI-enabled tools to accelerate validated analysis while building reusable playbooks and scalable self-service reporting capabilities.

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.

Analyze customer behavior across digital and phone journeys, develop experiments and OKRs, and translate data into actionable recommendations. Partner with product, technology, design, modeling, and analytics teams to improve customer experiences and operational efficiency. Present insights to senior stakeholders, support predictive analytics and machine learning initiatives, and maintain data governance through collaboration with data owners.

Leads enterprise data and analytics strategy, architecture, modernization, and delivery across cloud and on-premises environments. Oversees data platforms, engineering, integration, governance, quality, lineage, security, and compliance. Partners with executives to define roadmaps and investments, manages cross-functional teams and vendors, enables AI/ML capabilities, and mentors data professionals while driving scalable, trusted data solutions and measurable business outcomes.

Designs and maintains scalable data infrastructure, ETL/ELT pipelines, canonical datasets, and AI context layers. The role improves data quality and alignment across sales and finance systems, investigates data inconsistencies, leads requirements through UAT and implementation, supports analytics self-service, and partners with cross-functional teams to deliver process improvements and reliable business data.

Manages programmatic analytics and insights for client accounts, leading measurement frameworks, brand lift studies, incrementality testing, and A/B experiments. Develops media and campaign strategies, communicates performance insights to clients, and supports pitches and QBRs. Oversees, mentors, and develops analysts while partnering with Product, Engineering, Sales, and Customer Success teams to improve measurement tools, campaign optimization, and analytical capabilities.

Owns fraud performance analytics for depository products, including monitoring losses, approval rates, false positives, customer friction, and risk metrics. Builds data models, transformation pipelines, dashboards, scorecards, and monitoring frameworks. Conducts fraud deep dives and develops optimized rules, policies, thresholds, models, and decision strategies. Partners with Product, Engineering, Machine Learning, Data Engineering, Fraud Operations, and Risk teams to improve fraud detection and support product launches.

Leads analytics strategy and technical delivery for clients, specializing in Adobe Analytics and Customer Journey Analytics. Conducts measurement workshops, defines KPI and implementation strategies, oversees tagging and data quality, guides experimentation, and reviews dashboards and insights. Advises senior stakeholders, manages and mentors consultants, supports proposals and account growth, and contributes to Adobe Experience Platform initiatives involving Target, RT-CDP, and AJO.

Leads end-to-end marketing analytics for small business acquisition campaigns, including opportunity sizing, targeting, experimentation, performance reporting, profitability, and ROI measurement. Partners with Marketing, Finance, Modeling, and Data teams to guide investment decisions and improve measurement rigor. Owns stakeholder delivery, data requirements, analytic frameworks, controls, and auditability while coaching junior analysts and translating complex findings into clear recommendations for senior audiences.

Leads Educate!’s performance metrics and data function, setting strategy, building an AI-native analytics team, and owning data architecture, engineering, collection, and analytics oversight. The role establishes self-service reporting, governs dbt and BigQuery quality, develops dashboards and decision tools, advances predictive analytics, and partners with Technology, Evaluation, Product, implementation teams, and the COO. It also requires developing leaders, improving data literacy, and ensuring teams use data to improve youth programs.

Build and optimize scalable ETL/ELT pipelines using Matillion, AWS, and Snowflake. Develop governed, certified Data Products for an enterprise Data Marketplace across bronze, silver, and gold data layers. Implement data quality, lineage, metadata, access controls, CI/CD, monitoring, and certification workflows. Collaborate with analysts, data scientists, AI/ML teams, product owners, and stakeholders; contribute to architecture, roadmap planning, code reviews, mentorship, and reusable engineering practices.

Develops and supports business intelligence and analytics solutions, including data models, datasets, dashboards, reports, and integrated analytics. Partners with business and IT teams on data warehouse and data lake design, governance, data quality, technology performance, and analytics adoption. Uses SQL and Python to extract and shape data, automates dataset monitoring, and incorporates statistical or predictive capabilities into BI solutions.