Top Senior Analytics Jobs in Hampton, VA

The Director, Research - Power Markets is responsible for leading the QA/QC process for long-term forecasting, advising leadership, and ensuring market insights are effectively integrated into forecasts.

Lead a team of analysts and data scientists embedded in sales to build rigorous pilot analyses, create executive-ready business cases, expand consultative analytics across the partner lifecycle, and publish industry insights while coaching and scaling the Solutions Analytics function.

The Chief Data Officer will lead the enterprise-wide data strategy, ensuring data quality and governance while driving AI initiatives and business value.

This role drives data-driven decision-making in product analytics, collaborating with cross-functional teams to generate actionable insights and evaluate new launches to enhance platform growth.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

As a Principal Data Analyst, you'll lead credit analytics efforts, develop forecasting models, and collaborate with multiple teams to enhance Upstart's credit platform.

The Senior Analytics Engineer will develop data pipelines, build models, and create dashboards to provide actionable insights for various teams. The role requires collaboration with multiple stakeholders to meet analytical needs and ensure data governance.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

The Senior Reporting & Analytics Consultant leads customer-focused reporting and analytics engagements, developing solutions, supporting implementations, and training clients, while ensuring project success.

The Staff Analytics Engineer will own the Financial Subledger Data Platform, build dbt models, implement data quality controls, and mentor a junior engineer, ensuring high operational reliability and cross-functional collaboration.

The Senior Manager, Risk Analytics will build and own Upstart's risk analytics program, managing Key Risk Indicators, data models, and reporting infrastructure for enterprise-wide risk monitoring and compliance. They will collaborate with risk owners and conduct data aggregation and reporting, supporting risk assessments and regulatory requirements.

Lead the marketplace analytics by optimizing monetization strategies, monitoring performance, creating dashboards, and analyzing supply-demand dynamics. Collaborate cross-functionally to drive engagement and profitability.

Design and automate partner-facing reporting systems, transform complex healthcare data into clear insights, present findings to external stakeholders, support partner success, and collaborate cross-functionally to scale analytics workflows and uncover operational and clinical trends.

The Senior Analytics Engineer will design and implement scalable data solutions for Finance Analytics, reconcile data accuracy, and collaborate across teams to enhance financial datasets and reporting workflows.

The analyst will own planning for launches, build forecasting models, partner with stakeholders, and drive data-driven decisions using AI and analytics.

Design, build, and maintain production ETL/ELT pipelines, analytics-ready data models, and cloud data infrastructure. Improve pipeline performance, data quality, governance, and migrate legacy systems to modern platforms. Collaborate with stakeholders to translate business requirements into reliable data products for project, financial, and operational analytics.

Design and build scalable data foundations, pipelines, semantic models, and AI-grounded tooling. Lead platform-level AE tooling, reusable dbt patterns, observability, cost strategies, and agentic AI workflows. Partner with stakeholders, guide team technical development, and drive cross-functional data initiatives from ambiguous problems to production.

Own and evolve Moxie’s semantic layer (dbt + Omni), build benchmarking and segmentation datasets, enable embedded AI-driven analytics, lead revenue reconciliation and data governance, partner with BizOps to deliver actionable metrics, and lay groundwork for predictive and prescriptive analytics.

Design and implement end-to-end Microsoft Fabric data solutions (ingestion, Lakehouse, warehouse, real-time). Create architectures, reusable frameworks, and governance patterns for insurance datasets. Lead ingestion pipelines, optimize performance/cost, integrate with Azure services and security, support regulatory compliance, and provide technical direction to engineering and analytics teams.

Design and implement end-to-end data solutions on Microsoft Fabric and Azure for insurance datasets. Build ingestion pipelines (batch, streaming, API), Lakehouse architectures, and data models. Enforce governance, security, compliance, and cost/performance optimizations while guiding engineers and stakeholders on architectural best practices.

Join the BizOps & Analytics team embedded in a core business area to define problems, build analyses and reports, design experiments, surface insights, and drive data-informed decisions end-to-end to increase customer growth and business scale.

Embedded on a core business unit, own end-to-end analytics: define problems, design metrics and experiments, pull and analyze data, build reports, surface insights, and drive recommendations to inform product, growth, AI, or partnership decisions. Influence stakeholders and execute on outcomes.

Embed with a core business area to define problems, build metrics, run analyses and experiments, generate actionable insights, and drive product, growth, AI, or partnership outcomes end-to-end.

Lead end-to-end analytics for an assigned business area (growth, product, AI, or partnerships). Define problems, build metrics, reports, experiments, and analyses, surface insights, and drive recommendations and execution to improve key business outcomes.