Top Senior Analytics Jobs in Columbus, OH

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 complex data engineering initiatives supporting global cybersecurity analytics. Designs data architectures, ingestion pipelines, governance standards, and quality processes; collects, transforms, and models traditional and big data; develops Power BI visualizations; and improves data reliability and accessibility. Provides technical consultation, mentors team members, documents systems, presents insights, and responsibly applies AI tools. Requires strong Python, Pandas, SQL, cloud, Snowflake, Airflow, ETL, API, data modeling, and governance expertise.

Lead analytics for small business insurance marketing by developing audience segments, targeting strategies, campaign measurement, and experimentation plans. Partner with marketing, insurance, analytics, and technology teams to align data definitions, build scalable data assets, diagnose analytical issues, and deliver executive-ready insights. Use Python, SQL, cloud platforms, and modern data warehousing to improve campaign performance, conversion, incrementality, and decision-making.

Supports portfolio planning and operational analytics for auto insurance program delivery. Analyzes capacity, forecasts, rollout sequencing, dependencies, and performance metrics; builds dashboards, schedules, and reporting tools; conducts scenario analysis; and recommends delivery trade-offs. Partners cross-functionally with program management, state management, data science, and technology teams to maintain realistic roadmaps and improve planning workflows using Power BI, Power Apps, JIRA, Excel, AI, and automation.

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.

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.

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.

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.

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.

Leads the design, development, and support of customer-focused data and business intelligence solutions, including data models, reports, dashboards, and self-service analytics tools. Partners with stakeholders and IT, promotes data governance and quality standards, supports data lake design, and develops scalable analytics products. Provides technical leadership, mentors team members, manages project deliverables, and applies data science concepts to generate predictive and prescriptive insights.

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.

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.

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 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.

As a Senior Commercial Insurance Analyst, you'll perform complex analyses on data to drive business performance and risk outcomes. You'll collaborate with various teams, generate actionable insights, and mentor junior analysts, all while fostering a data-driven culture and improving operational efficiency.

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.