Top Remote Data & Analytics Jobs in Detroit, MI

Develop and maintain Python-based data applications and pipelines: fetch data from databases/APIs/files, build Pandas DataFrames/NumPy arrays, write complex SQL and data transformations, handle nested JSON, and collaborate with data science teams to deliver production data platforms.

Remote entry-level Big Data Engineer role building data acquisition and munging pipelines. Requires strong Python3 (NumPy, Pandas), advanced SQL, scalable algorithm and data-structure implementation on distributed clusters, converting code to functional paradigms, and the ability to learn PySpark or Kafka quickly. Product-development, startup experience and real-world pipeline projects preferred.

Lead data-focused Salesforce initiatives: engage stakeholders, assess and map legacy data, define migration and governance strategies, execute migrations using ETL/Data Loader tools, validate data through testing and reconciliation, and support reporting, analytics, and user enablement in Agile environments.

Analyze business processes, gather stakeholder requirements, identify improvement opportunities, and deliver data-driven recommendations. Collaborate with cross-functional teams to ensure solutions align with business goals and support implementation through clear communication and presentations.

Analyze datasets to generate reports and visualizations that inform business decisions. Produce regular reporting, create data visualizations, and work cross-functionally to support data-driven strategies with attention to accuracy.

Design and deliver reusable supply-chain analytics products and persona-based dashboards using the modern data stack. Partner with operations and customers to prioritize requests, leverage AI to accelerate analysis, and tie insights to measurable business outcomes. Support data maturity, integration, and agile product delivery.

Provide operational database support by executing predefined SQL scripts, performing data provisioning and cleanup, managing Azure Storage and ADS document loads, deploying reports, handling user access, participating in go-live events and 24x7 on-call rotations, and documenting tasks for audit readiness under senior SME guidance.

Lead product analytics to inform product strategy and growth: partner with PMs, engineers, and designers; build dashboards and measurement frameworks; perform quantitative analyses on large datasets; define KPIs and event tracking; translate insights into product solutions; and manage and grow a product analytics team.

Build and maintain backend services and scalable, parallelized data pipelines for Recruiting AI. Productionize microservices exposing classifiers/ML models, design message-based APIs, ensure enterprise SLAs, CI and test suites, and collaborate with data scientists, DevOps, product and engineering teams to integrate services into production.

Extract, clean, and transform data from multiple sources; build and optimize dashboards and reports; perform root cause analysis and statistical modeling; collaborate with leaders and Data Engineers to translate business needs; streamline data workflows and perform database migrations and schema mapping.

Own and maintain data products end-to-end for sector teams, analyze large datasets, refine methodologies, automate workflows using AI and tooling, collaborate with Research, Engineering, and Product, and deliver accurate, client-facing insights and improvements.

Support Practice Success by collecting, analyzing, and reporting operational health data; build dashboards and visuals; maintain project plans and trackers; map processes and identify workflow improvements; coordinate stakeholders and provide day-to-day project support to drive execution.

Lead lifecycle marketing analytics for co-brand and enterprise portfolios: identify growth opportunities, build dashboards and models, advise partners, automate scalable analytics, and promote data-driven decisioning to improve campaign ROI and customer experience.