Top Analytics Jobs in Columbus, OH

Evaluate Business Banking deposit and cash management products using data-driven analysis. Develop pricing strategies, analyze small-business banking behavior, create dashboards and reports, build data assets, automate processes, and provide insights for product development. Collaborate with Product, Design, and Technology teams, participate in senior product reviews, and present recommendations to business leaders.

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.

Analyze business data, uncover operational improvement opportunities, and develop automation and self-service solutions. The role partners with stakeholders and subject matter experts, performs ad hoc analysis, communicates actionable insights, and leads simplification projects. It requires experience with analytics and automation tools including Alteryx, Tableau, SAS, SQL, Python, Snowflake, AWS, APIs, and AI/ML concepts. This is an onsite role five days per week and does not offer visa sponsorship.

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.

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.

Leads marketing data and analytics initiatives that improve audience targeting, campaign execution, measurement, and operational reliability. Translates business objectives into technical requirements, designs data and audience management approaches, develops quality monitoring and reporting, manages issue resolution, and partners with Product and Technology on platform enhancements. The role also identifies responsible AI applications, establishes governance and controls, and supports measurable, repeatable delivery across digital marketing channels.

Leads People Analytics enablement and BI strategy, overseeing semantic models, certified data products, metric governance, data foundations, advanced analytics enablement, demand prioritization, and adoption. Partners with People Analytics, IT, and HR Strategy teams to create trusted workforce data, reusable semantic assets, and decision-ready insights. Manages teams and operating models while driving data quality, governance, certification, self-service analytics, AI access, and scalable insight delivery across the enterprise.

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.

Lead financial reporting delivery and data pipeline operations while improving data controls, quality, lineage, audit readiness, and regulatory compliance. Automate manual workflows using Alteryx, Python, and SAS; resolve production issues; partner with Technology on data models, testing, and enhancements; and analyze datasets for stakeholder reporting. Contribute to metadata, data dictionaries, responsible AI, and scalable data modernization initiatives.

Lead and manage the control environment for Data Privacy and Data Governance initiatives across CDAO. Conduct process reviews, identify risks, design and implement controls, support audits and regulatory exams, partner with legal/compliance/audit and firmwide control teams, and manage a high-performing team to sustain data governance, data privacy, and operational risk practices.

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.

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 Toast’s analytics engineering function, owning enterprise data architecture, modeling strategy, analytics-layer development, and AI-ready semantic-layer vision. Builds and manages a team of analytics engineers, establishes roadmaps, partners with data engineering and business leaders, and drives scalable, governed data solutions across domains. Requires expertise in data modeling, dbt, SQL, stakeholder alignment, and people leadership.

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.

Leverage data analytics, business intelligence, and data science techniques to deliver strategic insights and solutions for clients. Build reports, dashboards, data pipelines, visualizations, and data architecture using tools such as Oracle BI, QlikView, Spotfire, and BIRT. Ensure data quality, manage stakeholder relationships, improve analytics processes, interpret complex datasets, and mentor junior team members while contributing to client projects and business strategy.

Leads executive-facing analytics for Home Lending Product Strategy, framing hypotheses, measuring impact, evaluating tradeoffs, and delivering recommendations and business cases. Coordinates analysts across matrixed teams, partners with Strategy, Product, Marketing, Finance, Originations, and Technology, conducts market and competitor research, and translates complex analysis into concise insights for senior decision-makers.