Top Remote Analytics Jobs in Detroit, MI

Designs and maintains scalable data infrastructure, ETL/ELT pipelines, canonical datasets, and AI context layers. The role improves data quality and alignment across sales and finance systems, investigates data inconsistencies, leads requirements through UAT and implementation, supports analytics self-service, and partners with cross-functional teams to deliver process improvements and reliable business data.

Own Eve’s go-to-market data models and semantic layer for governed metrics including pipeline, conversion, CAC, win rate, ARR, and bookings. Establish certification frameworks, modeling standards, documentation, alerting, and analytical application patterns across the organization. Partner with Sales, Marketing, Customer Success, and RevOps stakeholders, resolve conflicting metric definitions, enable AI-grounded data tools, review contributions, and mentor analytics engineers.

Analyze and optimize drug pricing using data-driven models, dashboards, reports, and strategic frameworks. Partner with Sales, Operations, Marketing, Finance, Product, pharmacy partners, and data teams to identify opportunities, define success metrics, improve reporting, and balance pharmacy economics with patient affordability. Serve as a trusted analytical advisor and support backend data development and query optimization.

Supports cross-channel marketing attribution and influence modeling by documenting data sources, defining business rules, mapping and normalizing interaction data, testing reporting prototypes, and recommending implementation steps. The intern also assists with AWS marketing data organization, segmentation research, data hygiene, process documentation, and stakeholder communications. The role requires analytical thinking, thorough documentation, clear communication, and collaboration across marketing and technical teams.

Leads enterprise data governance strategy, transformation, operating model modernization, accountability, and executive engagement. Partners with senior stakeholders to improve data trust, accessibility, regulatory alignment, risk management, analytics, AI readiness, and business outcomes. Represents the Data Office in strategic and regulatory forums, establishes roadmaps and performance measures, resolves cross-functional data challenges, and drives organizational change without direct authority. The role focuses on governance and transformation rather than engineering, coding, analytics delivery, or technical administration.

Leads a client-facing healthcare analytics team that designs and maintains prior authorization decision automation programs. Consults PaaS clients, develops strategic roadmaps, translates requirements into technical blueprints, analyzes authorization and claims data, and builds KPI reports using visualization tools. Manages direct reports, improves analytics processes and AI tooling, partners with product and engineering teams, and ensures automation outcomes and client KPIs are achieved.

Own Hometap’s product and marketing event-data ecosystem, including taxonomy, tracking plans, governance, Segment Protocols, schema validation, and source management. Partner with marketing, product, and engineering to define instrumentation and event specifications. Build monitoring for schema conformance, event volume, and property completeness, while documenting standards and managing event review and deprecation processes.

Leads an eight-person analytics engineering team and sets strategy for trusted semantic models, governed data, enterprise BI, AI-powered data access, and production data applications. Oversees data modeling, evaluation datasets, telemetry, LLM routing, governance, security, and self-service capabilities. Partners cross-functionally to establish engineering standards, roadmaps, and measurable business impact while hiring, coaching, and developing team members.

Build Deepgram’s governed decision layer above warehouse gold tables. Responsibilities include modeling cross-system entities, owning semantic and metrics definitions, creating agent-facing data tools and MCP surfaces, implementing data quality assertions and reconciliation checks, evaluating AI agent accuracy, and answering business questions while leaving reusable models behind. The role requires production-grade SQL and Python, semantic-layer ownership, strong data modeling judgment, AI-native workflows, clear writing, and comfort building infrastructure from scratch.

Build and maintain scalable data transformation pipelines, analytics-ready datasets, data warehouses, data marts, and reusable data models using SQL and dbt. Implement data quality testing, validation, monitoring, documentation, and governance while optimizing warehouse performance and integrating multiple data sources. Partner with analysts, product managers, and business stakeholders to support dashboards, KPI reporting, business intelligence, and strategic analytics initiatives.

Owns a six-month analytics engineering engagement covering scalable Snowflake architecture, marketing and sales ingestion, finance automation with LLM agents, data reconciliation, and governed Tableau reporting. Builds production-ready pipelines, data models, quality monitoring, human-in-the-loop controls, and row- and column-level security. Delivers documentation and knowledge transfer while coordinating independently with finance and publishing stakeholders.

Maintains and monitors Azure Databricks data pipelines, troubleshoots data issues, collaborates with stakeholders on data requirements, documents processes, performs backups and disaster recovery drills, and supports data access and usage. The role requires extensive data engineering experience, Azure expertise, incident management knowledge, and strong problem-solving skills.

Provides technical leadership for enterprise analytics by architecting SQL-based transformations, scalable data models, semantic layers, and governed datasets. Builds analytics products supporting healthcare KPIs, patient journeys, scheduling, retention, and operational decisions. Establishes analytics engineering standards, testing, documentation, lineage, and code-review practices; troubleshoots data-quality issues; partners with business and technical stakeholders; and mentors analysts in SQL, dimensional modeling, dbt, and governed data-product development.

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 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.

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.

Supports Somali-speaking learners in a fully virtual data analytics program. Responsibilities include answering questions, facilitating breakout rooms, holding office hours, reviewing materials, grading assignments, providing feedback, recording walkthroughs, monitoring learner progress, and escalating concerns. The role also requires supporting live sessions, communicating in Somali and English, attending onboarding and staff meetings, and submitting weekly progress reports.

Owns the enterprise Snowflake data platform end to end, including architecture, ingestion, transformation, security, governance, reliability, performance, cost optimization, and AI enablement. Establishes engineering standards, reviews architecture, resolves complex production issues, mentors data professionals, and leads cross-functional adoption of scalable, governed analytics capabilities. The role provides senior technical influence without direct people management and supports secure MCP-based AI integrations.

Leads and manages an analytics engineering team while contributing to data transformation, modeling, quality, and delivery solutions. Establishes modeling and development standards, implements analytics engineering tools, supports client engagements, improves reporting and visualization processes, allocates team resources, mentors engineers, supports presales, and drives internal quality and process improvements.

Analyzes business and operational needs, gathers requirements, evaluates data and systems, and recommends technology solutions. Develops advanced SQL queries, reports, system models, and process improvements. Responsibilities include troubleshooting, data architecture integration, software and hardware solution design, database analysis, automation using scheduling or RPA tools, and project leadership. Senior levels guide other analysts and assess technology’s business impact.

Owns analytical projects across customer onboarding, transaction behavior, and platform operations. Designs dashboards, KPI frameworks, reporting workflows, and data pipelines while delivering actionable insights. Partners with Engineering, Product, Payment Operations, Compliance, and Finance; mentors colleagues; manages project scope and priorities; resolves ambiguity; and drives cross-functional alignment. Requires advanced SQL and data modeling skills, BI tool experience, analytical scripting familiarity, FinTech domain knowledge, and 4+ years of analytics experience.

Lead analytics partner to Community Support, driving data-driven roadmaps, scalable reporting and measurement, causal inference and experimentation, and improvements to agent/guest/host experiences via analytics, modeling, and stakeholder influence.

Build and maintain production data pipelines that transform robot logs and telemetry into reliable, queryable datasets. Design Spark-based ETL workflows, orchestrate processing with Airflow or similar tools, manage gold-layer datasets, and implement data quality, schema evolution, monitoring, and metadata practices. Collaborate with robotics, hardware, reliability, analytics, and ML teams on data modeling, fleet insights, debugging, and root-cause analysis. The role may also contribute to Python, Java, or C++ libraries supporting data capture and consumption.

Leads enterprise data and analytics strategy, architecture, modernization, and delivery across cloud and on-premises environments. Oversees data platforms, engineering, integration, governance, quality, lineage, security, and compliance. Partners with executives to define roadmaps and investments, manages cross-functional teams and vendors, enables AI/ML capabilities, and mentors data professionals while driving scalable, trusted data solutions and measurable business outcomes.

Supports healthcare implementation projects, business workflow documentation, process improvement, work plans, and deliverables. Reviews large datasets from multiple sources to identify outliers, monitor trends, and prepare state-mandated reports. The internship provides experiential learning for undergraduate students interested in healthcare or data analytics.