Top Analysis Reporting Jobs in Hampton, VA

Lead architecture and execution of Faire's data platform and analytics capabilities. Build and operate scalable, secure ETL/ELT, streaming, storage, compute, orchestration, and data warehousing at petabyte scale. Drive performance, cost, monitoring, governance, and self-serve analytics; influence cross-functional teams and mentor engineers.

Lead a small analytics team (staff data scientist + two analysts) to deliver curriculum, product, and program insights. Split time between people management (60-70%) and hands-on analysis (30-40%), advance experimentation and measurement, build AI/LLM-driven agentic workflows, manage sprints and cross-functional stakeholder relationships, and drive analytics that inform curriculum, product, and intervention strategies.

Design and maintain a dbt-based business data layer for GTM metrics, centralize and reconcile multi-source data, implement automated data quality and reconciliation checks, align and document metrics with stakeholders, mentor analytics team, and lead root-cause investigations into complex data anomalies.

As a Senior Data Scientist at Yahoo Mail, you will enhance user growth strategies via product innovation, overseeing research projects and analytics.

Designs and operates scalable serverless AWS data pipelines, data models, ETL/ELT workflows, feature stores, and analytics-ready data assets. Partners with AI, Analytics, Product, and Underwriting teams to support reproducible ML training and scoring, MLOps, data quality, monitoring, governance, and production troubleshooting. The role handles sensitive healthcare and financial data, optimizes serverless workloads, supports batch and near-real-time processing, and applies infrastructure-as-code, CI/CD, documentation, and responsible data-use practices.

Forecasts call volumes, handle times, and service metrics; develops staff schedules; analyzes workforce and performance data; prepares reports; monitors real-time call and agent activity; performs ad hoc and operational analyses; and communicates recommendations to management regarding staffing, scheduling, service levels, and operational initiatives.

Own Backblaze’s analytics transformation and semantic layers using dbt and Snowflake. Build governed data models, certified metrics, lineage, testing, documentation, and auditable financial-reporting data products. Establish engineering standards and scalable delivery practices while partnering with Data Engineering, Finance, Revenue Operations, Marketing, and Business Intelligence. Translate ambiguous reporting needs into trusted entities, metrics, and source-of-truth models, with emphasis on data quality, stakeholder adoption, and AI-ready foundations.

Leads WWT’s Data Reliability and AI Readiness pillar, setting enterprise AI data strategy and standards for trustworthy, reusable data. Oversees certification, lineage, quality SLAs, readiness scoring, data products, dashboards, and AI-powered reporting. Coordinates IT, AI engineering, analytics, business, and data teams on enterprise initiatives. Manages a Product Owner and engineers, improves operational data, promotes certified data products, and translates internal AI and data capabilities into customer-facing value.

Designs, develops, optimizes, and maintains enterprise data platforms, databases, ETL workflows, reporting solutions, and business intelligence systems. Leads technical design, SDLC processes, production troubleshooting, documentation, stakeholder collaboration, and automation efforts. Requires advanced Microsoft SQL Server, T-SQL, and SSIS expertise, plus experience with data warehousing, BI, dashboards, and Microsoft DevOps. Cloud data services, APIs, Microsoft BI tools, and Python or Java are preferred or advantageous.

Designs, develops, and optimizes enterprise data platforms, databases, ETL workflows, data integrations, reporting, and business intelligence solutions. Leads technical designs, automated process improvements, production troubleshooting, documentation, and dashboard development. Collaborates with stakeholders and vendors, supports scalability and cloud migration, and participates in an off-hours support rotation. Requires advanced SQL Server, SSIS, T-SQL, SDLC, and data engineering expertise.