Top Senior Data & Analytics Jobs in Detroit, MI

Lead Voice of Customer practice through survey and listening-program design, fielding, vendor coordination, data-quality oversight, and synthesis. Manage enterprise insights repositories, decisions journals, methodology libraries, and knowledge-transfer rituals. Maintain VoC and knowledge-management platforms, establish taxonomy and metadata standards, coach peers on research quality and documentation, and ensure organizational insights remain discoverable, credible, and reusable across staff transitions.

Designs and implements Google Cloud database migration strategies, including architecture, data models, database objects, pipelines, orchestration, security, and data transfers. Advises customers on Cloud Spanner and Cloud SQL implementations, translates SQL and stored procedures, configures Google Cloud components, performs performance testing, resolves performance issues, and delivers technical workshops and architectural recommendations.

Develop and optimize marketing reports, monitor product and advertising campaign KPIs, integrate and visualize data, investigate performance deviations, analyze campaigns, and recommend improvements. The role requires strong Google Sheets skills, basic SQL, A/B testing, mathematical statistics, and English proficiency. Python, web analytics, Google Ads, and BI experience are preferred. This is a fully remote position.

Leads supply chain analytics, reporting, automation, and Power BI solutions while managing product readiness portfolios for launches and product changes. Coordinates cross-functional deliverables, governance forums, SKU readiness, risk escalation, documentation, and milestone tracking across commercialization projects. Translates business needs into scalable analytics and digital solutions, communicates insights, and drives stakeholder adoption and operational improvements.

Leads the design and implementation of AI-powered data pipelines, enterprise feature stores, analytics-ready repositories, and self-service data access layers. Builds automated feature engineering, data quality, observability, and governance capabilities for large-scale data science workloads. Partners with Enterprise IT, establishes data availability and quality SLAs, integrates structured and unstructured data sources, and leads teams delivering scalable analytics infrastructure.

Design and build petabyte-scale multimodal data pipelines and infrastructure (text, audio, images, video). Own and maintain systems like Spark, Ray, and vector databases, partner with pre/post-training teams to improve data recipes through experimentation, and support large-scale dataset storage and processing for AI model training.

Leads the Sales Analytics and Reporting function and manages Sales Analysts. Oversees dashboards, scorecards, KPI tracking, profitability analysis, business insights, executive reporting, and sales technology platforms. Partners with Sales, Finance, Product, Technology, and other stakeholders to improve performance, profitability, planning, and decision-making. Develops team capability, reporting processes, platform adoption, and analytical effectiveness while translating complex data into actionable recommendations.

Reviews AI-generated documents, spreadsheets, and slide decks for accuracy, rigor, presentation quality, and domain-specific compliance. Evaluates outputs using quality rubrics, identifies factual and aesthetic errors, and provides structured written feedback. The role requires deep expertise in data quality and CRM operations, strong English fluency, and proficiency with Microsoft Office and Google Workspace. It is a fully remote, flexible independent-contractor engagement.

Analyzes, cleanses, validates, and prepares operational datasets for mailing, email, reporting, billing, and processing activities. Develops Databricks queries and Alteryx workflows to automate processes and improve data quality. Performs audits, reconciliations, root-cause analysis, and corrective actions while maintaining governance and security compliance. Provides actionable insights, mentors junior analysts, communicates findings, and leads continuous improvement initiatives.

Own Kepler’s transaction data feed end-to-end, ensuring accuracy, improving methodologies, developing QA frameworks, solving complex analytical problems, and prototyping enhancements. Analyze massive datasets, automate workflows with AI, evaluate client-facing AI outputs, address high-complexity customer questions, and collaborate with Research, Product, Data Science, and Engineering teams.