Top Senior Data & Analytics Jobs in Detroit, MI

The Product Analyst will measure results and deliver insights on new AI products, identify opportunities, and guide product strategy through data analysis and visualization.

The Solutions Consultant will conduct product demos, assist in sales cycles, and provide evidence of product value while maintaining product knowledge and client relations.

The Sector Lead for Financial Services will oversee channel research projects, ensuring quality and relevance while guiding a team of analysts. Responsibilities include developing questionnaires, managing research workflows, and expanding coverage across financial services sectors.

Analyze revenue and growth performance, provide insights on auction behavior, measure A/B tests, define KPIs, and perform root-cause analysis.

The Data Analyst will support operational reporting and stakeholder needs, working with SQL and Artiva to meet business requirements through data and reporting solutions.

The Senior Data Engineer will maintain and improve data infrastructure, design ETL processes, and create high-performance pipelines for analytics and AI initiatives using SQL and Python in cloud environments.

The Senior Data Engineer will design and maintain data pipelines, write production-grade Python and SQL code, and support AI initiatives while collaborating across teams.

The Senior DataOps Engineer oversees data management and storage systems, ensuring timely access to secure and accurate data, improving data workflow automation, and collaborating with teams to meet business needs.

The Senior Consultant will lead the design and implementation of data solutions using Microsoft Fabric, Power BI, and Databricks to enhance analytics capabilities for clients. They will engage with stakeholders to define data strategies and deliver high-quality consulting services across multiple projects.

The Revenue Analytics Lead drives data analytics and modeling for revenue operations, overseeing GTM performance metrics, predictive modeling, and data governance while utilizing AI for operational efficiency.