Top Remote Data & Analytics Jobs

Analyze telematics, IoT, sensor, and firmware data to evaluate hardware performance, reliability, and field issues. Build dashboards and reports, identify trends and anomalies, apply statistical and machine learning techniques, validate firmware improvements, and provide actionable insights to engineering, product, data science, and customer support teams. Help develop scalable data pipelines and promote data-driven hardware and software development.

Owns the strategic direction, prioritization, and governance of an enterprise data domain. Coordinates Data Stewards, Data Custodians, business leaders, and enterprise data product teams to improve data quality, accessibility, compliance, alignment, and adoption. Leads domain working groups, prioritizes data issues and products, aligns cross-domain initiatives, translates business needs into data specifications, and escalates conflicts when necessary.

Lead analytics for Wealth Solutions: analyze client segmentation, revenue, and operational data; build models for capacity and workforce planning; produce insights and recommendations for senior leadership; partner with BI and Finance to improve advisor productivity, client experience, retention, and revenue growth; support strategic projects and translate complex data into clear presentations.

Manages Finance analytics engineering and automation, building governed Snowflake and SQL data products, consumption layers, reconciliations, controls, workflows, and integrations. Partners with FP&A, Data Engineering, and business teams to translate Finance requirements into reliable technical solutions. Leads lineage analysis, testing, monitoring, documentation, AI-assisted workflows, production support, and team development while maintaining clear ownership between Finance and enterprise data teams.

The Associate Director will lead AHP’s analytics and data products domain, building curated datasets, transformation pipelines, semantic models, dashboards, and automated reporting. Responsibilities include delivering client and enterprise data products, establishing reporting standards, managing production refreshes and documentation, coordinating data engineering resources, and supporting AI initiatives. The role is hands-on, client-facing, and requires technical leadership across distributed project teams.

Leads Lexia’s business analytics and data strategy function, managing analysts and overseeing data engineering alignment. Owns BI strategy, Tableau governance, data governance, self-service dashboards, AI-enabled analytics, metric definitions, and data quality. Partners with Sales, Marketing, Customer Success, executives, and analytics engineering to translate business needs into insights, KPIs, models, and actionable recommendations. Manages analytics tools and vendors while ensuring responsible, secure, and effective use of enterprise data.

Leads enterprise data and actuarial technology strategy, modernization, architecture, delivery, operations, and production support. Owns cloud data platforms, actuarial applications, analytics, governance, resilience, controls, budgets, vendors, workforce planning, and regulatory readiness. Partners with actuarial, insurance, business, and technology leaders to execute multiyear roadmaps, modernize legacy systems, improve data quality and self-service analytics, and deliver measurable business value. Builds and leads a high-performing technology organization while overseeing risk, service health, disaster recovery, and operational performance.

Analyze complex data to support business decisions across marketing, finance, product, sales, medical affairs, and customer success. Responsibilities include defining data requirements, developing and automating data pipelines, building interactive dashboards, identifying trends and process improvements, and presenting insights to executives and external partners. The role requires advanced SQL, Python, BI, visualization, and cross-functional analytics experience, with an emphasis on using AI to improve efficiency.

Leads analytics for B2B sales, partnerships, revenue operations, and marketing teams. Responsibilities include forecasting, opportunity sizing, partner performance analysis, enterprise market intelligence, RFP analytics, lead scoring, funnel and lifecycle optimization, predictive modeling, experimentation, and executive insight generation. The role partners with Data Science and Engineering teams to improve revenue growth, onboarding, retention, campaign effectiveness, and sales performance across enterprise and SMB channels.

Build and maintain production-grade data models while migrating workflows from Alteryx to dbt. Manage Dagster or Airflow pipelines in Redshift, create Tableau dashboards, and translate technical data into RevOps insights. Partner with Sales, Marketing, and Customer Experience leaders on KPI reporting, ABM, and customer health scoring. Explore AI, LLM, predictive analytics, and SageMaker machine learning applications including churn prediction and lead scoring.