Top Remote Data & Analytics Jobs in Ann Arbor, MI

Analyze data and build analytical datasets, data models, dashboards, reports, and visualizations using Databricks, SQL, Python, and BI tools. Translate business requirements into reporting solutions, validate data quality, identify insights, document analytical logic, and support governance, security, lineage, and compliance. Collaborate with engineers, data scientists, architects, clients, and other stakeholders to deliver accurate, secure, and well-documented analytics solutions.

Supports analytics product improvements by researching data issues, designing reports, documenting business requirements, developing use cases, and conducting user acceptance testing. The role creates training materials, facilitates user training, supports credit unions and internal users, promotes business intelligence practices, and helps transition analytics solutions into business operations.

Leads business intelligence, workflow automation, and data stewardship for financial risk operations. Builds governed Tableau and Power BI reporting environments, develops Python, SQL, RPA, and ETL solutions, analyzes trends, and delivers predictive insights. Maintains audit-ready controls, data integrity, version management, error handling, and compliance. Partners with stakeholders to modernize manual processes, improve efficiency, track operational performance, and scale self-service analytics.

Leads marketing and enrollment analytics across acquisition and conversion funnels. Analyzes channel performance, ROI, attribution, forecasting, experimentation, and marketing mix modeling; develops recommendations for budget allocation and performance improvement. Uses Power BI, SQL, Python or R, and institutional and marketing datasets to build models, automate monitoring, identify anomalies, and support cross-functional decisions. Owns marketing measurement standards, data quality, tracking, and analytical roadmap while partnering with Marketing, Enrollment, Field, and Institutional Analytics teams.

Develops acquisition fraud analytics and strategies for home and auto platforms. Responsibilities include building analytic solutions, creating automated reports and performance summaries, conducting impact analyses, analyzing client and population data, and tracking champion/challenger strategy tests. The role partners with cross-functional stakeholders, presents insights to senior leadership, and supports credit and fraud initiatives using SAS, SQL, Unix, Excel, and VBA.

Analyze banking and financial crime data, develop and tune statistical and machine learning classification models, evaluate model performance, identify data quality issues, and recommend optimization strategies. The role uses Python and SQL for feature engineering, statistical modeling, automation, and large-scale data processing. Responsibilities also include documenting methodologies, reporting results to management and regulators, and collaborating with compliance, technology, business, and model governance teams.

Senior Decision Scientist partners with product, engineering, marketing, and finance teams to guide roadmaps, resource allocation, and business strategy. The role uses experimentation, causal inference, statistical analysis, metric strategy, and user behavior research to produce actionable recommendations. Responsibilities include establishing causality, improving instrumentation, communicating insights to leadership, and using AI tooling to scale analytical workflows. The position requires consumer technology analytics experience, strong SQL and Python or R skills, and expertise in experimentation and causal inference.

Designs and leads enterprise data pipelines and integrations across Snowflake, Oracle Fusion, on-premises databases, and cloud applications. Ensures data quality, governance, security, scalability, and performance while supporting Power BI, AI/ML, and self-service analytics. Partners with business and technical stakeholders, leads migrations, mentors engineers, optimizes data platforms, and establishes engineering best practices.

Designs, builds, deploys, and maintains scalable data pipelines, data lake systems, batch and streaming processing, MLOps frameworks, data documentation tooling, and an agentic data exploration platform. The role supports customer-facing products and enables engineering teams through reliable infrastructure, observability, data discovery, and AI capabilities.

Leads CookUnity’s Advanced Analytics function, setting strategy and partnering with Product, Finance, Operations, Marketing, and leadership. The role involves experimentation, causal inference, retention and growth analysis, marketing measurement, product impact evaluation, and translating insights into business decisions. This hands-on player-coach will guide complex analytical work, develop analysts, improve analytical rigor, and shape team structure and priorities.