Top Analytics Jobs in Columbus, OH

Leads complex data engineering initiatives for global cybersecurity analytics. Designs data architectures, ingestion pipelines, governance standards, and quality processes; collects and transforms large datasets; develops Power BI visualizations; improves data reliability and accessibility; documents systems; advises stakeholders; mentors team members; and responsibly applies AI tools to improve workflows while protecting confidential data.

Leverage data analytics, business intelligence, and Python to deliver strategic insights and tailored solutions for clients. Build reports, dashboards, data pipelines, and support data architecture and quality initiatives. Analyze data from multiple sources to identify trends, improve operations, and inform decision-making. Collaborate with stakeholders and team members while continuously developing technical skills and contributing to process improvements.

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.

Analyze wealth management client, advisor, market, and financial flow data to support strategic and regulatory decisions. Use SQL, Python, R, statistical methods, causal inference, and machine learning to investigate trends, evaluate competitors, and detect anomalies. Translate complex analyses into clear recommendations for stakeholders and senior leaders across business, finance, legal, and analytics functions.

Lead programmatic analytics for clients and internal teams by analyzing campaign and model performance, designing tests, developing measurement solutions, recommending optimizations, and presenting actionable insights. Partner with Sales, Customer Success, Product, Engineering, and clients to align marketing strategies, reporting requirements, and optimization efforts with business goals.

Leads the strategy, architecture, implementation, and evolution of enterprise analytics platforms. Responsibilities include designing scalable data platforms, integrating digital and enterprise data, establishing governance and security standards, optimizing analytics and BI capabilities, evaluating cloud technologies, managing platform performance and risks, and mentoring technical teams. The role also requires close collaboration with executives, clients, Product, Engineering, Data Science, Marketing, and business stakeholders.

Lead and scale Runpod’s analytics and business intelligence function, managing analysts and BI practitioners while setting the analytics roadmap. Own core company metrics, consumption and marketplace analytics, self-service reporting, experimentation practices, and executive and board-level insights. Partner with Product, Finance, Engineering, Security, Supply, and Go-to-Market leaders to improve data quality, modeling, decision-making, and strategic outcomes.

Design and maintain analytical data models, transformation frameworks, data-quality checks, semantic definitions, and metric consistency across analytics and customer-facing products. Partner with engineering, product, and analytics teams to document data, improve lineage, and enable trustworthy self-service data usage. The role requires advanced SQL, analytics engineering, dimensional modeling, testing, and collaborative translation of business concepts into precise data definitions.

Leads analytics for Pricing and Supply, managing a team of approximately eight analysts. Partners with cross-functional leaders to prioritize analytical work, build dashboards and decision frameworks, improve metric quality, and generate insights into pricing, supplier coverage, marketplace performance, conversion, margin, and customer behavior. Coaches analysts, establishes scalable analytics processes, and collaborates with data engineering teams to improve data models, tooling, and self-service capabilities.

Leads a 15+ person analytics organization supporting Growth, Sales, Marketing, and Finance. Owns the analytics strategy, operating model, metric governance, executive reporting, forecasting, experimentation, customer and revenue insights, and data foundation improvements. Partners with senior commercial and financial leaders to translate complex data into strategic recommendations and builds scalable processes, systems, and talent development programs.

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.

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.

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.

Own end-to-end data products, including source onboarding, API and file-feed ingestion, orchestration, incremental and idempotent pipelines, Snowflake and dbt Cloud modeling, testing, documentation, alerting, and production reliability. Establish engineering standards, manage secrets and governance, use AI coding tools responsibly, collaborate with vendors and stakeholders, and mentor junior engineers.

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.

Develop and maintain dashboards, reports, scorecards, KPI solutions, and analytical models that provide business performance insights. Responsibilities include trend and root-cause analysis, forecasting, data validation, stakeholder requirements gathering, reporting automation, process improvement, documentation, and data quality governance. The role partners with cross-functional teams and communicates findings to technical and non-technical audiences.

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.

Leads General Liability insurance pricing analytics, predictive modeling, model governance, and data science strategy. Develops, validates, deploys, and monitors advanced statistical and actuarial models supporting underwriting, profitability, and pricing decisions. Partners with actuarial, underwriting, product, claims, finance, and technology teams; communicates recommendations to senior leaders; manages complex projects; and leads, coaches, and develops analytical staff.

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 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.