Top Senior Level Analysis Reporting Jobs in Minneapolis, MN

The Application Systems Analyst aids businesses in achieving their goals by evaluating, designing, and developing full stack application systems. Responsibilities include developing applications on FileMaker, consulting with management, creating application specifications, overseeing implementation, diagnosing errors, and managing reported incidents.

The Workday Lead Analyst will design, develop, and maintain Workday integrations and reports, support HR and Finance functions, and ensure the smooth operation of Workday systems. Responsibilities include system maintenance, report development, user training, and participation in project management.

As a Staff Data Scientist at Coinbase, you will build advanced models, provide technical mentorship, and develop novel experimentation techniques to drive business value. Your role will involve creating sequential features based on user behavior and quantifying the impact of negative experiences on the platform.

As a Data Engineer, you will design, build, and maintain data pipelines and integration processes while collaborating with data scientists and analysts to ensure efficient data flow across the organization.

The Workday Reporting & Analytics Principal Consultant will lead the design and implementation of analytical solutions within Workday, mentor other consultants, support HCM and financial implementations, and engage with clients to analyze requirements and provide solutions. The role emphasizes customer service and expert reporting skills to deliver superior results.

The Principal Researcher will enhance research by analyzing publications, evaluating research ideas, implementing prototypes or production software, and communicating findings. The role requires collaboration with researchers and the application of knowledge in cryptography, distributed systems, and algorithms.

As a Senior Data Scientist at StackAdapt, you'll focus on building predictive models to enhance business operations, identify high-potential customers, and implement time series forecasting. The role requires collaboration with internal teams and coding production-ready algorithms. You need a strong data science background and a willingness to turn ambiguous tasks into actionable steps.