Top Senior Data & Analytics Jobs in Des Moines, IA

The specialist will guide customers in cloud data warehousing transformations, provide technical leadership on big data projects, and assist in architecting production-level data pipelines with a focus on performance tuning and data modeling.

The Insights Lead Analyst will develop analytics strategies, connect data for insights, and deliver actionable recommendations to clients, enhancing marketing decisions based on data analysis.

As a Principal Data Analyst, you'll leverage machine learning and AI to improve outcomes, manage large data sets, and guide analytics modelers for effective data solutions.

The Senior Product & Growth Analyst will lead the analytics behind Trust & Will's growth, focusing on conversion, retention, and lifetime value analysis. Responsibilities include building predictive models, conducting experimentation, and delivering data-driven recommendations to stakeholders. The role involves collaborating across product, marketing, and growth teams, with a strong emphasis on user behavior and funnel analysis.

The Senior Clinical Data Manager oversees clinical trial databases, mentors junior staff, and ensures data quality and compliance with regulatory standards.

The Lead, Advanced Analytics, Acquisition will analyze data, define metrics, conduct A/B tests, and collaborate with teams to drive growth and insights.

Lead the design of DataOps platforms, focusing on scalable data infrastructures and automation frameworks. Oversee robust data orchestration and establish quality frameworks.

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.