Top Remote Analysis Reporting Jobs in Des Moines, IA

As the Director of Analytics, you'll lead analytics for MyPrize, optimizing performance across teams, developing reporting tools, and informing data infrastructure.

Design and customize Sage Intacct, develop financial reports, support data migration, and train users while ensuring compliance with GAAP.

The Senior Product Analyst will oversee product analytics projects, collaborating with teams to develop KPIs, conduct A/B testing, and provide data-driven insights to enhance decision-making.

The Senior Data Analyst will conduct quantitative analysis, optimize products through data insights, and lead A/B testing in collaboration with various stakeholders.

As a Curriculum Manager, you will manage the content development lifecycle, collaborate with instructors, and improve data science curriculum, ensuring technical accuracy and pedagogical effectiveness.

Design, build, and maintain end-to-end data pipelines and ETL/ELT for healthcare data using Snowflake, dbt, Python, and SQL. Ensure data quality, monitor production jobs, troubleshoot anomalies, write dbt models and tests, collaborate with Analytics/Operations/Clinical teams, and participate in Agile processes with GitLab and Jira.

Senior member of the Data & Analytics team who translates operational reporting requirements into Epic- and Qlik-based analytics solutions. Develops RW SQL reports, Radar dashboards, and self-service artifacts; validates data, mentors junior analysts, enforces best practices, supports intake/prioritization, and coordinates training and legacy-to-new-tool migrations.

Perform data analysis on complex spreadsheets, benchmark and research data to identify trends and insights. Collaborate with writers, engineers, and strategists to validate and implement findings, create charts and visualizations, and deliver timely, client-facing deliverables as a US-based freelance contractor.

Build and maintain reports, dashboards, and visualizations; analyze data to provide actionable insights; support ad hoc requests; ensure data quality with engineers; document processes; integrate AI tools to streamline cleaning, analysis, and documentation; collaborate with stakeholders to track outcome-based metrics.

Lead and scale the enterprise data hub: manage the data warehouse, build reliable ingestion and transformation pipelines, implement governance and data modeling best practices, deliver GTM-ready metrics, enable AI/ML use cases, prioritize the data roadmap, and lead/mentor a data engineering team.