Top Remote Data & Analytics Jobs

Leads Relation Insurance’s enterprise data engineering and analytics function, owning data strategy, architecture, pipelines, governance, quality, reporting, and AI-enabled workflows. The role requires hands-on development in SQL, Python, and PySpark, executive communication, technical team leadership, lakehouse architecture, Power BI modeling, production support, and secure data management. The director also directs AI coding agents, builds LLM-powered workflows, establishes engineering standards, and delivers reliable data products aligned with business priorities.

Conduct pretesting, item analysis, IRT, score maintenance, data extraction, statistical reporting, and quality control for SAT assessments. Develop and maintain Python and R-based data management and statistical workflows, improve operational processes, document procedures, and evaluate AI-enabled tools. Collaborate with psychometricians and cross-functional teams to deliver accurate assessment data and reports under strict deadlines.

Analyzes card fraud threats by gathering and interpreting transaction data, quantifying losses, evaluating fraud rules, monitoring suspicious activity, and recommending control improvements. The role produces reports and presentations, supports automation, data governance, model monitoring, quality audits, and ad hoc business analysis. It partners with fraud, data governance, and model governance teams to improve detection effectiveness and reduce financial losses.

Build and maintain Power BI dashboards, reports, data models, pipelines, ETL/ELT processes, and data warehouses. Develop advanced DAX and SQL solutions, optimize performance, implement security and governance, manage Fabric and Power BI deployments, and integrate diverse data sources. Translate business requirements into technical solutions while collaborating with end users on testing and implementation. The role also requires strong visualization, data quality, documentation, communication, and automation skills.

Generates business, market, customer, and competitive insights for enterprise strategy and growth initiatives. Analyzes healthcare trends, customer needs, market opportunities, and competitive dynamics; builds forecasts, market models, and scenario analyses; synthesizes research, voice-of-customer data, and internal analytics; and presents executive-ready recommendations. Provides analytical and project support to marketing and PMO teams while translating customer insights into strategic actions.

Collects, processes, and analyzes data from multiple sources using R, Python, and SQL. Develops reports, visualizations, analytical methods, and data-driven insights while applying statistical and introductory machine learning techniques. Collaborates with internal and external stakeholders, documents project progress in JIRA, debugs code, clarifies requirements, and communicates findings through reports and presentations.

Serve as the technical authority for enterprise SQL Server administration and database engineering. Manage configuration, upgrades, patching, performance, security, backups, disaster recovery, and high availability. Design schemas, optimize T-SQL, enforce data integrity, and establish retention policies. Lead incident root-cause analysis, database initiatives, documentation, and continuous improvement while collaborating with DevOps, infrastructure, engineering, QA, and product teams. Mentor developers and maintain highly available, secure, and recoverable production databases.

Analyzes business processes, coordinates application implementations and projects, facilitates stakeholder meetings, documents requirements and procedures, supports testing, and helps resolve technical and business challenges. Requires knowledge of business analysis practices, Agile development, SDLC, project coordination, Microsoft Office, COBOL or IBM i environments, and SQL Server or DB2.

Analyze and transform complex data into targeted audiences and actionable marketing insights. Responsibilities include audience strategy, acquisition opportunity analysis, testing frameworks, advanced SQL querying, ETL monitoring and troubleshooting, data visualization, and stakeholder presentations. The role collaborates cross-functionally to deliver data-driven solutions aligned with client objectives and performance targets.

Lead migration to a Databricks lakehouse using dbt, design ELT pipelines, improve ingestion reliability, establish data quality and governance, and build analytics- and AI-ready datasets. The role owns platform architecture, access controls, monitoring, documentation, data contracts, and legacy-system retirement. It partners with engineering, data science, AI, analysts, and business stakeholders while mentoring engineers and influencing technical standards.