Top Remote Data & Analytics Jobs in Des Moines, IA

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

Design and govern end-to-end data architecture for an integrated supply-chain e-commerce platform: create data models, build scalable ETL/ELT pipelines, ensure GDPR-compliant data governance, enable real-time analytics, optimize databases, plan retention/archival, and prepare data for LLM fine-tuning and RAG use cases.

Build and operate trusted data products, governed datasets, scalable pipelines, and platform workflows supporting analytics, AI, and business operations. Responsibilities include data quality, validation, observability, recoverability, semantic consistency, governance controls, permissions, privacy-aware access, automation, and production monitoring. The role partners with stakeholders to resolve ambiguous data needs, drives platform improvements, provides technical direction, and adopts agentic development workflows.

Reviews video annotations, action labels, and hand-pose data for accuracy, consistency, and completeness. Corrects errors using detailed quality guidelines, evaluates English-language descriptions, documents findings, and provides feedback on recurring issues. The role requires methodical visual review, precise corrections, clear written communication, and independent work in a remote environment. No prior AI experience is required.

Leads College Board’s Operations analytics strategy and team, developing forecasting, predictive modeling, optimization, cost assessment, and decision-support capabilities. Partners with senior leaders across Operations, Product, Program, Technology, and Finance to improve execution, customer experience, efficiency, and cost savings. Responsibilities include setting technical direction, embedding analytics into operational decisions, presenting insights, hiring and coaching analytics staff, and building future AI and data-infrastructure capabilities.

Paid actuarial internship supporting Actuarial Operations and Predictive Analytics teams. Responsibilities include gathering information, organizing data in spreadsheets and databases, performing basic analysis, collaborating on projects, and communicating findings to actuarial leaders. The intern will build knowledge of insurance operations, statistics, data management, and programming, with potential for continued part-time employment based on performance and business needs.

Develop and maintain data ingestion pipelines, relational databases, ETL/ELT workflows, cloud resources, data reliability monitoring, and AI-enhanced applications. Integrate LLM APIs and MCP connectors, write Python and R automation code, migrate siloed processes into centralized systems, and collaborate with technical and non-technical stakeholders. The role also supports Azure deployments, enterprise data integrations, dashboards, reporting, and cloud data security.

Own healthcare analytics data methodology, including episode grouping, provider attribution, cost standardization, quality measures, reference data, pipelines, QA, and production delivery. Translate feature requests into specifications and validated analytics. Reconcile results, establish recurring data-quality coverage, investigate failures, and collaborate with engineering, data science, product, clinical informatics, and customer teams. Advanced SQL and healthcare claims expertise are central to ensuring accurate, defensible customer metrics.

Lead partner analytics by building scalable dashboards, forecasting and ROI models, and experimental designs to evaluate and optimize partner performance. Collaborate with Product, BD, Marketing, and Data Engineering to improve pipelines, translate insights into recommendations, and mentor analysts to scale partner growth.

Own analytics for Customer Success and Operations by translating ambiguous business questions into metrics, reports, dashboards, and PRDs. Partner with senior leaders, CSMs, Analytics Engineers, and Operations teams to improve retention, permit turnaround, and organizational scalability. Build self-service dashboards, develop dbt models, document analytics assets, prioritize high-impact requests, and use LLM tools to accelerate SQL, reporting, and data-model development.