Top Senior Data & Analytics Jobs in Des Moines, IA

The role involves developing forecast models for oncology products, collaborating with teams, and communicating assumptions for strategic decision-making across the organization.

Develop, maintain, and improve predictive models and operational forecasts to support claims demand and capacity planning. Build Python workflows, prepare and validate data with SQL and Python, automate manual processes, create visualizations and BI solutions, and partner with stakeholders to translate business questions into analytical solutions while sharing knowledge with teammates.

Design, build, and automate scalable batch and streaming data pipelines, implement data models and ETL, automate deployments, support ML/experimentation, maintain server architecture, and partner with stakeholders to deliver analytics and data-driven tools.

Lead and manage institutional research activities: collect, analyze, validate, and report quantitative and qualitative data; support program/course reviews, accreditation, dashboards, and decision-making; supervise a team and manage ad-hoc and ongoing reporting and assessment projects.

The Staff Data Scientist will lead analytical strategies for Firefox, focusing on product growth, measurement frameworks, and mentoring data scientists while guiding data-driven decisions.

The Senior Data Analyst role involves data collection, analysis, dashboard creation, and collaboration with various teams to inform business decisions and optimize processes.

The Senior Analyst, Revenue Operations is responsible for delivering analytical insights, enhancing forecasting accuracy, and optimizing revenue processes while collaborating with various departments.

As a Senior Data Engineer, you will design and maintain data warehouses, ensuring data quality, manage data transformations, and mentor others while partnering with various stakeholders.

The ETL Architect is responsible for designing ETL architectures, development, and implementation of data models and warehousing solutions, with a focus on data quality and transformation logic.

The VP of Data will lead the data organization encompassing engineering and analytics, drive strategic insights, improve operational excellence, and integrate AI into workflows while ensuring data governance.