Top Remote Data & Analytics Jobs in Detroit, MI

Leads AlphaSense’s Financial Services channel research coverage across banking, insurance, and fintech. Develops coverage roadmaps, channel-check frameworks, expert source strategies, and structured questionnaires. Guides analysts and operations teams on project execution, expert targeting, feasibility, and research quality. Acts as the primary financial services domain expert, identifying companies, subsectors, value chains, and research opportunities while improving workflows and ensuring insights are consistent, actionable, and aligned with investor demand.

Leads client-facing database migration and modernization engagements across AWS, relational, and NoSQL platforms. Designs migration architectures, data pipelines, ETL/ELT workflows, proof-of-concepts, and reusable technical accelerators. Facilitates executive conversations and workshops, translates complex technical solutions into business outcomes, and supports pre-sales opportunities. The role also develops GenAI-enabled migration tooling, influences senior stakeholders, and collaborates with distributed engineering, product, and data teams.

Develops healthcare reporting and analytics solutions using Power BI and SQL to improve operational and clinical performance. Responsibilities include gathering requirements, validating data quality, creating dashboards and reports, partnering with data engineering and advanced analytics teams, training users, maintaining documentation, managing reporting timelines, and resolving data or logic issues.

Lead the design and optimization of healthcare data pipelines integrating EHR, payer, HIE, and vendor data. Build AWS-based ETL/ELT infrastructure, reusable integration tooling, data quality monitoring, and ML enablement foundations. Ensure HIPAA-compliant handling of clinical data, including security controls, audit logging, encryption, and de-identification. Provide technical leadership, mentor engineers, influence platform architecture, and lead complex partner integrations involving FHIR, HL7v2, CCDA, and healthcare terminology standards.

Owns governance, quality, standards, and lifecycle management for eight master data domains across ERP and related systems. Administers NetSuite master data, defines validation and error-proofing controls, resolves data discrepancies, maintains audit-ready documentation, and reports quality KPIs. Partners with IT, Supply Chain, Finance, Commercial, Regulatory, Customer Care, and other teams on integrations, migrations, product launches, compliance, serialization, and pricing. Provides cross-functional guidance and drives data discipline without direct authority.

Conducts operations research and advanced analytics to optimize public-sector command performance and reduce costs. Develops optimization, statistical, simulation, regression, mathematical, and decision-analysis models; implements analytical models in Python; performs data analysis; supports software development; assesses operational questions; and prepares decision briefings, reports, presentations, and recommendations for senior leadership.

Conduct forensic analytics for anti-money laundering and financial crime monitoring. Analyze large transactional datasets with SQL and Alteryx, identify suspicious behaviors and emerging typologies, develop and validate detection scenarios, calibrate thresholds, perform lookbacks and segmentation studies, evaluate transaction networks, and support AML investigations, SAR narratives, and regulatory responses.

Own and evolve Worldly’s production data lake, Postgres warehouse, CDC and streaming pipelines, dbt transformations, orchestration, BI access controls, and graph integrations. Maintain reliable, governed analytics infrastructure using Iceberg, Trino, Dagster, Terraform, and AWS. Support production generative AI workflows involving embeddings, similarity search, extraction, and classification. Responsibilities include data quality, monitoring, security, incident response, disaster recovery, schema governance, and collaboration with data science and analytics stakeholders.

Leads advanced analytics initiatives supporting sales, marketing, and operations strategy. Develops statistical and predictive models, dashboards, KPI reporting, and customer analyses using large datasets. Partners with stakeholders and data engineering teams to translate business questions into actionable insights, communicates findings to executives, and mentors junior analysts.

Develop and maintain data engineering solutions using Informatica Data Management Cloud, Control-M, Snowflake, and SQL. Responsibilities include sourcing, transforming, cleansing, ingesting, analyzing, and visualizing data; building automated workflows and scalable ETL processes; supporting data architecture and deployments; and delivering reusable code for large datasets. The role requires collaboration with technical and business partners, troubleshooting, mentoring, and managing multiple priorities.