Top Remote Analysis Reporting Jobs in Columbus, OH

Leads data transformation and governance for the Personal Lines Product, Pricing, and Underwriting domain. Develops data roadmaps, translates plans into epics, guides modernization onto a new technology stack, governs data policies and regulatory protections, and coordinates stakeholders across business and technical teams. The role requires strong insurance data expertise, knowledge of complex data models and warehousing, Agile collaboration, and experience with platforms such as Guidewire PolicyCenter.

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.

Build and maintain production data pipelines, Airflow DAGs, Snowflake infrastructure, and Data Vault 2.0 models. Ensure data quality, observability, security, governance, reliability, and cost efficiency through automated testing and CI/CD. Lead technical projects end-to-end, collaborate with stakeholders, and support SOX-relevant reporting while developing expertise in commercial insurance data and processes.

Leads healthcare analytics projects using clinical, claims, pharmacy, and eligibility data to evaluate cost, utilization, quality, and program performance. Develops statistical analyses, predictive models, dashboards, and reporting solutions; identifies optimization opportunities; partners with clinical, product, engineering, and business teams; presents recommendations to stakeholders; and mentors junior analysts.

Define and govern enterprise-scale data architecture across batch, streaming, warehouse, lakehouse, transactional, and AI use cases. Establish standards for data quality, lineage, access, cataloging, governance, observability, and SLAs. Architect AI-enabled workflows, resolve complex architecture issues, influence roadmaps, and mentor engineers through hands-on technical leadership. The role requires 15+ years of software, data engineering, or architecture experience and expertise in large-scale data platforms and modeling.

Leads business performance analytics and reporting initiatives, developing Power BI dashboards, KPI frameworks, scorecards, forecasts, and actionable insights. Partners with business leaders to translate needs into reporting solutions, performs root-cause and trend analysis, validates data, establishes governance standards, and mentors analysts. The role combines hands-on reporting development, analytical problem-solving, performance measurement, and cross-functional initiative leadership.

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.

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 customer listening and Voice of Customer programs, including NPS, CSAT, CES, surveys, and interviews. Analyze qualitative and quantitative customer data to identify drivers, trends, pain points, and opportunities. Present insights to executives and cross-functional teams, facilitate action planning, and drive systemic customer experience improvements. Evaluate AI tools for sentiment analysis, theme extraction, and customer research while helping build a data-driven, customer-centric culture.

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.