Top Data & Analytics Jobs in Detroit, MI

As a Cultural Analyst, you will uncover cultural insights and trends, shaping strategies for clients, while conducting research and synthesizing findings into actionable strategies.

Lead statistical programming for clinical trials, managing programmers and CROs. Oversee programming activities, ensuring timely support for clinical projects and developing programming processes.

The Instructional Designer I creates high-quality online courses, interacts with various teams, and requires strong communication and project management skills.

The Sr State Product Analyst provides analytical support for strategic goals, analyzes performance data, and implements processes for financial planning and market development.

The Principal Statistical Programmer supports Epidemiology by preparing Real World data, conducting analyses, programming data tools, and liaising with stakeholders on multiple projects. Responsibilities include creating analytical databases, producing reports, and managing relationships with clients and investigators.

The Senior Salesforce Business Analyst will align GTM technology strategies with business goals, optimize processes, enhance Salesforce configurations, support integrations, and drive user adoption while facilitating cross-team collaboration.

The Applied Data Scientist will manage client engagements, unifying datasets, building models, deriving insights, and collaborating with teams to implement solutions.

Drive marketing performance measurement and attribution by building dashboards, standardizing campaign tracking across HubSpot and Salesforce, running funnel and cohort analyses, ensuring data integrity, and delivering executive reporting to connect marketing activity to pipeline and revenue.

Lead technical consultant responsible for data lineage solutions and MANTA configuration. Collaborates with teams to support data governance and ensure accurate lineage documentation.

The Senior Data Engineer will design and build data models, manage data pipelines, improve data quality, and collaborate with teams to deliver reliable data solutions for the company.