Top Remote Analysis Reporting Jobs in Columbus, OH

Build and maintain web crawling and scraping pipelines to collect, transform, and deliver third-party healthcare data. Research sources, assess feasibility, implement extraction strategies, test for quality, and maintain scrapers when sources change. Participate in weekly standups and initial fundraising activity.

Analyze complex content, datasets, research questions, and logical problems; verify claims through online research; summarize information; evaluate and correct AI-generated responses; and create annotations and scenarios to improve large language model performance. The role is fully remote, full-time for 16 weeks, requires U.S. English fluency, independent work, strong analytical and research skills, and an existing Gemini account with relevant conversation history.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

Build and maintain ETL/ELT pipelines, ingest and transform structured and unstructured data, integrate APIs and external sources, improve data quality and monitoring, support dashboards and ML pipelines, optimize warehouse and cloud performance, and contribute to data governance and documentation.

Leads complex private banking data management and analytics initiatives, defining data strategies, quality standards, product attributes, and integrated client views. Partners with business, engineering, analytics, AI, and Wealth teams to translate needs into dashboards, KPIs, predictive models, personalized insights, and intelligent decision-making capabilities. Serves as a subject matter expert on private banking products while mentoring junior team members and enabling platform readiness.

Supports DHA MEPRS cost-accounting activities through recurring data processing, validation, reconciliation, analysis, reporting, and customer support. Extracts and analyzes personnel, workload, financial, and other datasets using SAS, Excel, and reporting repositories. Investigates data-quality issues, troubleshoots root causes, documents findings, develops recurring and ad hoc analytical products, communicates results, and improves or automates processes.

Design, build, and maintain scalable data pipelines, data lakes, and databases; ingest and map customer financial datasets; monitor pipeline reliability; translate business requirements into data flows and analytical insights to ensure high-quality, usable data.

Support design, development, and maintenance of data pipelines and infrastructure. Assist with ETL/ELT workflows, data ingestion, cleaning, validation, modeling, and warehousing. Document processes and collaborate with data teams to support analytics use cases.

Performs advanced product and business analytics for a consumer mobile app, including experimentation, statistical analysis, metric development, dashboards, and leadership-ready insights. Partners with Product, Engineering, Finance, Data Science, and Analytics teams to guide strategy and feature iteration. Works independently with large datasets, communicates tradeoffs clearly, and uses AI-assisted tools to improve analytical efficiency.

Owns B2B and B2C funnel, enrollment, revenue, and marketing performance reporting. Builds executive and Board dashboards, analyzes CAC, LTV, retention, conversion, spend efficiency, and ROI, and reconciles marketing activity with financial results. Maintains KPI definitions and reporting governance while partnering with Marketing, Finance, FP&A, Sales Operations, and Data teams. Supports strategic planning, diligence requests, and actionable business recommendations through accurate, cross-functional analytics.

Define and lead enterprise data architecture centered on Snowflake, including source integration, ingestion frameworks, data modeling, governance, security, compliance, quality, lineage, and AI-ready data products. Build reference pipelines using AWS and Snowflake services, establish engineering standards, optimize performance and costs, and guide architecture decisions. Partner with analytics and AI teams, lead reviews, mentor engineers, and influence stakeholders across the organization.