Top Analysis Reporting Jobs in Greensboro, NC

Leads marketing experimentation, conversion optimization testing, incrementality analysis, marketing mix modeling, and statistical measurement programs. Designs rigorous experiments, manages SQL-based testing databases, validates data, develops executive reporting, and translates complex findings into investment and marketing recommendations. Partners with marketing, product, technology, analytics, and executive teams while potentially mentoring junior analysts.

Design and operate Alpaca’s scalable data platform on GCP, including lakehouse infrastructure, Kubernetes-based deployments, streaming and CDC pipelines, batch ingestion, BI access, cataloging, monitoring, and governance. Build infrastructure as code with Terraform and Ansible, operate distributed query engines and Apache Iceberg, maintain reliability practices, and collaborate with DevOps and analytics teams to support rapidly evolving data requirements.

We are seeking an experienced data analyst to maximize our service offerings through data mining, generation, and visualization, while producing goal-oriented reports.

Develop statistical, machine learning, and deep learning models to measure the impact of pharmaceutical HCP, DTC, and Medical Affairs campaigns. Partner with internal and external clients, provide analytical insights and methodological guidance, consult with sales and market research teams, and coach an offshore analytics team. The role requires applying causal inference, healthcare and pharmaceutical data expertise, and clear communication of findings to clients and executives.

Lead client-facing analytics implementations across Google Analytics 4, Adobe Analytics, and tag management systems. Responsibilities include designing measurement strategies, auditing digital ecosystems, managing tagging and consent platforms, developing data governance and privacy solutions, analyzing performance, aligning KPIs with business goals, presenting insights, supporting proposals, and improving internal analytics standards. Preferred experience includes server-side tagging, data clean rooms, customer data platforms, experimentation, CRM systems, and ETL tooling.

The Sr. Data Modeler designs and implements data architectures, optimizes SQL queries, and develops data pipelines to support analytics initiatives ensuring scalability and alignment with business needs.

Own marketing channel performance analysis, reporting, experimentation, dashboards, and measurement frameworks. Develop incrementality, LTV, and forecasting analyses; identify data quality risks; and translate complex findings into actionable recommendations for Marketing, Growth, and Finance stakeholders. The role requires strong SQL, BI reporting, marketing measurement, experimentation, and analytical communication skills, with AI tools used to accelerate analytics workflows.

Lead advanced product analytics for a consumer product team by analyzing complex data, designing experiments, applying statistical and causal inference methods, developing metrics and reporting tools, and delivering actionable recommendations to cross-functional stakeholders and senior leadership. The role requires strong Python or R and SQL skills, product analytics experience, AI-assisted analytics proficiency, and the ability to influence product strategy.

Develop business intelligence and analytics solutions using financial, operational, RF, and video performance data. Build scalable data models, dashboards, reports, automation workflows, and ETL/ELT processes using Power BI, Tableau, DataMiner, and Qligent. Analyze trends and anomalies, monitor satellite and video delivery performance, translate business requirements into actionable insights, and collaborate with enterprise stakeholders in a fully remote consulting role.

Guide customers through data integration and migration, analyze data quality, identify and resolve anomalies, support validation and system synchronization, and document troubleshooting practices. The role communicates recurring data trends to product and engineering teams, improves operational processes, and enhances customer self-service. It requires professional QuickBooks experience, customer-facing technical support or onboarding experience, strong communication, and problem-solving skills.