Top Remote Artificial Intelligence Data & Analytics Jobs

Design and deploy object detection and tracking modules; develop ML algorithms; guide team members; improve data governance and quality assessment.

Define and drive the enterprise data architecture and roadmap, lead large-scale data platform and data mesh design, enforce modeling, lineage, governance, and quality standards, advise executives and stakeholders, and embed AI/LLM-assisted workflows to scale analytics, reporting, and AI/ML use cases globally.

Lead scaling of Arbital's AWS/Databricks lakehouse and Spark pipelines, implement actuarial healthcare calculations, own Airflow orchestration and CI/CD, ensure data quality and HIPAA-compliant PHI handling, partner with data scientists to deploy ML models, and set platform architecture and engineering standards.

Design and maintain enterprise revenue-cycle KPIs and dashboards, analyze multi-source RCM datasets, build predictive models, identify process improvements, support audit/compliance, lead stakeholder working groups, author executive deliverables, follow PM best practices, mentor junior analysts, and safeguard PHI/PII under DoD controls.

Embedded analytics partner on BizOps & Analytics team: define problems, build metrics and reports, run analyses and experiments, surface insights, and drive cross-functional decisions to improve growth, product, AI/automation, or partnerships.

Embed within a core business unit to define problems, build analyses and reports, design experiments, surface insights, and drive data-informed decisions end-to-end across growth, product, AI, or partnerships.

Responsible for creating and maintaining technical documentation for developers, ensuring clarity and effectiveness in conveying product capabilities and usage. Collaborate with engineering and growth teams to enhance resources while gathering feedback for continuous improvement.

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.

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, build, and optimize SQL Server-based data layers and Azure data solutions. Own query performance, indexing, concurrency, CDC pipelines, ORM data access patterns (C#), and database CI/CD. Partner with engineers and architects, mentor team members, and ensure scalable, low-latency data platforms.