Top Data Management Jobs in Denver & Boulder, CO

Lead the development of analytics solutions across operations, manage a team of analysts, and drive operational excellence and decision-making through data insights.

The Data Manager will support partners by addressing data needs, managing issues, and implementing best practices for effective data use in civic engagement campaigns.

Lead and manage a team of data engineers, oversee data warehouses and pipelines, ensure scalable data architecture, and foster partnerships with data analysts and scientists.

Lead a data science team to develop insights from autonomous vehicle data, create scalable platforms for data access, and collaborate with cross-functional teams on performance measures.

The Senior Manager, Data Science & Analytics will lead a team to drive analytics and experimentation strategies for Yahoo Mail's growth and monetization, engaging with product, finance, and marketing to transform data insights into actionable strategies for success.

The Manager, Data Analysis oversees centralized monitoring for clinical trials, ensuring effective RBQM systems, data analysis, and reporting while collaborating with cross-functional teams.

The Fundraising Data Manager will manage data processing for clients, develop custom SQL scripts, create reports, and manage client CRM.

The Senior Manager RBQM Data Analyst oversees centralized monitoring activities for clinical trials, utilizing data analysis tools to assess risks and operational performance, while leading process improvements and training junior staff.

Lead a data science team to enhance Netflix's streaming product through analytics and experimentation, partnering with engineering.

Lead a data science team to drive consumer acquisition strategies and improve Netflix's signup processes through analytics, experimentation, and machine learning.

Lead clinical data management for studies, oversee CROs, ensure data quality, coordinate data review, and assist in clinical system implementations.

Lead a team of Data Scientists, Analytics Engineers, and Data Engineers to drive messaging strategies through analytics and data science, ensuring collaboration across various business domains.

The Senior Data Manager will design, configure, and launch clinical trials on Citrus while managing data quality and collaborating with product teams and stakeholders.

As a Data Manager, you will oversee data management for clinical trials, ensuring quality outcomes, designing data capture tools, and collaborating on product development.

This role involves leading data projects, managing analytics, delivering insights, and mentoring team members while collaborating on data strategies for clients.

Manage marketing data systems, track pipeline and revenue analytics, ensure data quality, and provide proactive insights. Collaborate with cross-functional teams to align on metrics and reporting.

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.

As a Data Analytics Manager, you will lead a team to analyze data, drive strategic insights, manage projects, and optimize mobile app performance for top brands.

The Data Analytics Manager analyzes complex datasets for private equity and corporate clients, providing insights for transactions, guiding due diligence, and mentoring junior team members.

Lead and mentor a Data Engineering team, manage data operations, ensure compliance with HIPAA, and design scalable ETL pipelines while collaborating across departments.

Lead AI and data initiatives to enhance marketing capabilities and drive growth. Collaborate across teams to optimize data usage for better performance and decision-making.

The Data Conversion Manager oversees new customer onboarding, facilitating data migrations to the Encompass Cloud Platform, ensuring quality and accuracy in data transfers across systems.

Manage a team of analysts while analyzing data, reporting, and enabling AI/ML model deployment. Provide insights and automate processes.

Manage a team of data scientists to develop fraud detection models, mentor staff, and collaborate with leadership on solutions and product development.

Lead and scale the data analytics function, manage a distributed analytics team, deliver actionable insights, and oversee analytics projects.