Top Senior Analytics Jobs in Greensboro, NC

Lead Client Legal Services analytics strategy and team development. Own Power BI reporting products, Microsoft Fabric data solutions, governance, predictive modeling, responsible AI adoption, ROI measurement, and executive insights. Partner cross-functionally to improve legal operations, litigation outcomes, staffing, capacity, cost management, quality, and workflow optimization while building scalable analytics capabilities and institutional knowledge.

Lead analytics and data science initiatives to drive measurable business outcomes across various functions, including Underwriting and Claims. Oversee the full analytics lifecycle, foster stakeholder engagement, and mentor junior team members.

Leads analytics strategy and technical delivery for clients, specializing in Adobe Analytics and Customer Journey Analytics. Conducts measurement workshops, defines KPI and implementation strategies, oversees tagging and data quality, guides experimentation, and reviews dashboards and insights. Advises senior stakeholders, manages and mentors consultants, supports proposals and account growth, and contributes to Adobe Experience Platform initiatives involving Target, RT-CDP, and AJO.

Designs and maintains standardized healthcare reporting and analytics solutions using Azure Databricks, SQL, and Power BI. Builds data transformations, reusable models, semantic datasets, metrics, visualizations, and governed reporting products. Partners with business, clinical, pharmacy, analytics, and technology stakeholders to translate complex requirements into scalable solutions. Explores AI-enabled and conversational analytics, including Genie One, while ensuring data quality, documentation, and maintainability.

Leads customer analytics, revenue and retention reporting, executive and board reporting, renewal variance analysis, capacity modeling, customer health scoring, churn prediction, and data governance. Partners with Finance, Sales, Revenue Operations, Product, and Customer leadership to standardize SaaS metrics, improve retention, forecast revenue, and translate complex datasets into strategic recommendations and executive-ready dashboards.

As a Revenue Analytics Manager, you will own reporting for Sales, Marketing, and Customer Success, build dashboards, automate workflows, and ensure data quality.

Lead design and implementation of tracking with GTM, analyze user behavior in GA4, build BigQuery queries and dashboards, define KPIs with cross-functional teams, troubleshoot tagging/data issues, and perform deep-dive conversion and journey analyses to optimize web and mobile performance.

Owns executive reporting for autonomous vehicle system performance, including the weekly Software Performance Review and broader commercial readiness analyses. Synthesizes robotics data, diagnostic evaluations, and performance metrics into strategic narratives for senior leadership. The role aligns cross-functional engineering data, automates reporting pipelines and presentation generation, establishes visualization standards, and mentors junior engineers. It requires deep knowledge of robotics, autonomous vehicle performance, data architectures, executive communication, and AI-assisted development workflows.

Performs audit-focused data extraction, analysis, and reporting using SQL, R, Python, SAS, Posit, and Snowflake. Supports internal and external audits, legal, compliance, and investigations by transforming complex datasets, identifying risks and trends, reviewing data models and process flows, and providing code feedback. Requires 5+ years of data analysis experience, a relevant bachelor’s degree, and strong querying and project management skills.

Build and operate Imagine Worldwide’s AWS- and ClickHouse-based analytics platform, including infrastructure, data lakes, Spark processing, ingestion pipelines, Airflow orchestration, dbt models, CI/CD, monitoring, security, backups, and cost optimization. Process billions of device events and integrate program context into reliable analytical datasets. The role also involves incident response, documentation, architectural contributions, and collaboration with globally distributed analytics and operations teams.

Analyze marketing and customer data to measure campaign impact, uncover customer insights, and improve marketing ROI. Build Tableau dashboards, write and optimize SQL queries, conduct segmentation and lifecycle analysis, validate data quality, and provide actionable recommendations. Partner with marketing, product, and analytics stakeholders to translate business needs into analytical solutions and support strategy across channels, including spend allocation, targeting, attribution, and campaign effectiveness.

Build and lead Surescripts’ commercial analytics function, including governed Salesforce and CRM data models, KPI definitions, dashboards, forecasting, pipeline analytics, customer journey insights, automated reporting, quota modeling, and territory planning. Manage an analyst and partner with Sales, Marketing, Finance, Data, and Business Applications. Present actionable recommendations to senior leaders while improving data quality and enabling self-service analytics.

Own end-to-end production data platforms, writing Python and SQL, designing AWS pipelines, modeling analytics data, and implementing quality and reconciliation controls. Make architecture decisions independently, ensure correctness and auditability, and use AI coding tools effectively. The role also supports applied AI initiatives including entity resolution, LLM-assisted analytics, embeddings, and anomaly scoring.

Data Engineer II will modernize BlueLabs’ data platform by leading Kimball dimensional modeling and legacy warehouse migrations, building reliable production data pipelines, and enforcing data quality standards. The role requires advanced SQL, Python, and dbt expertise, hands-on Snowflake and Redshift experience, and ownership of testing, documentation, observability, and scalable architecture. The engineer will collaborate cross-functionally, guide Data Engineer I team members, contribute to architectural decisions, and translate business logic into maintainable, cloud-agnostic data layers.

Own analytics and reporting solutions for acquisitions, product launches, and other complex business events. Translate business changes into data models, system updates, processes, and reporting definitions. Coordinate Data Engineering, Analytics, Data Science, and Data Governance teams; lead cross-functional execution and establish a Business Intelligence Council. Partner across GTM, Finance, Product, IT, and other functions to reconcile metrics, clarify ownership, and maintain business visibility.

Lead analytics support for Fetch’s Food and Beverage vertical, serving as the primary analytics partner for Sales and client stakeholders. Own sub-vertical partnerships, manage analytic capacity, answer senior-level client questions, and guide campaign strategy. Use SQL to manipulate data, develop actionable insights, support QBR storytelling, and communicate recommendations to technical and non-technical audiences. Represent analytics cross-functionally and automate insights using AI-enabled tools.

Leads marketing and loyalty analytics strategy, measurement frameworks, forecasting, experimentation, campaign reporting, retention analysis, churn modeling, and segmentation. Partners with Marketing and Finance to establish performance goals and translate complex data into actionable recommendations. Automates reporting using analytics platforms, marketing automation tools, experimentation methods, and AI-enabled workflows while identifying opportunities to grow and retain high-value consumers.

Owns B2B and B2C funnel, enrollment, revenue, and marketing performance reporting. Builds executive and Board dashboards, analyzes CAC, LTV, retention, conversion, spend efficiency, and ROI, and reconciles marketing activity with financial results. Maintains KPI definitions and reporting governance while partnering with Marketing, Finance, FP&A, Sales Operations, and Data teams. Supports strategic planning, diligence requests, and actionable business recommendations through accurate, cross-functional analytics.

Lead insurance risk analytics engagements for property and casualty carriers. Responsibilities include product demonstrations, regulatory filing guidance, pilot and proof-of-concept design, loss ratio and model validation analysis, client project management, discovery sessions, and translating insights for actuarial, underwriting, and executive audiences. The role also develops AI-assisted workflows and provides customer feedback to product teams.

Lead and scale companywide analytics for a DTC marketing business: own marketing measurement, financial forecasting, retention/LTV modeling, data architecture, reporting, and the analytics team. Set analytics strategy, oversee data engineering roadmap, build dashboards, apply statistical and ML methods, and translate insights into executive-level decisions.

Analyzes healthcare claims, provider reimbursement, QPA, and dispute data to support No Surprises Act negotiations, arbitration, and OON liability management. Builds SQL-based reports, dashboards, data processes, and financial views; validates data quality; tracks dispute KPIs; integrates internal and external sources; and presents actionable recommendations to leadership and cross-functional stakeholders.

Analyzes paid media performance across the full funnel, connecting spend and platform metrics to applications, enrollment, student lifetime value, and ROAS. Builds attribution frameworks, Databricks data pipelines, Power BI dashboards, semantic models, and advanced DAX reporting. Supports marketing mix modeling, experimentation, web analytics data quality, forecasting, governance, and workflow automation. Translates complex analytics into strategic recommendations for executive and cross-functional stakeholders.

Build and operate trusted finance data products, pipelines, models, reconciliations, dashboards, and automation. Partner with Finance, Accounting, Data Engineering, Product, and Platform teams to resolve data issues, improve reporting, support financial close, establish data lake quality controls, and enable timely insights. Use SQL, Python, dbt, Spark, Airflow, and AI-assisted tools to deliver tested, traceable, production-ready solutions.

Lead and scale Runpod’s analytics and business intelligence function, managing analysts and BI practitioners while setting the analytics roadmap. Own core company metrics, consumption and marketplace analytics, self-service reporting, experimentation practices, and executive and board-level insights. Partner with Product, Finance, Engineering, Security, Supply, and Go-to-Market leaders to improve data quality, modeling, decision-making, and strategic outcomes.

Build and maintain product data models, ELT pipelines, semantic layers, and self-service analytics assets. Partner with Product Engineering and Data Governance to define canonical data, certify metrics, document taxonomies, monitor data quality, and support expansion and upsell analytics. Translate business requirements into governed data products, communicate insights to technical and non-technical stakeholders, and ensure data tooling complies with federal frameworks including FedRAMP and DoD IL4/5.