Top Remote Data & Analytics Jobs in Pittsburgh, PA

The Credit Bureau Business Analyst will manage bureau execution and analysis, support product onboarding and compliance controls, and drive data quality improvements through data analysis and cross-functional collaboration.

Support sales intelligence by collecting, preparing, and analyzing sales and marketing data; maintain dashboards and data quality; run pipeline and win/loss analyses; translate findings into clear visualizations and reports for stakeholders.

Lead analytics work translating complex healthcare data into decision-ready insights. Own KPI definitions, Snowflake data marts with dbt, executive dashboards in QuickSight, and cross-functional analyses to inform strategy, product, and operations.

The Market Risk Analyst will monitor SBL lines of credit, assess market risks, manage collateral, develop risk models, and prepare reports.

As a Data Engineer, you will design and maintain data pipelines, build data storage systems, and support analytics workflows, ensuring data reliability and performance. You will collaborate with engineers to define data structures and improve data management practices.

Support commercial decision-making by transforming internal and external data into actionable insights. Maintain recurring performance reporting, conduct market and competitive analyses, build dashboards and automations, and produce executive-ready insight summaries to inform pricing, promotion, innovation, and supply chain planning.

The AV Safety Analytics Engineer will develop data analytics infrastructure for automated vehicle safety, utilizing cloud processing and statistical methods. Responsibilities include creating data visualizations, monitoring metrics, and ensuring data integrity across systems.

The Revenue Strategy & Planning Manager will develop actionable growth plans by analyzing data, building reports, and collaborating with Sales leaders to enhance B2B revenue strategies.

The RevOps Manager is responsible for optimizing sales execution through data analysis, CRM management, enablement initiatives, and strategic support for growth goals.

Lead fraud detection efforts by analyzing data, developing detection methods, collaborating with teams, optimizing fraud rules, and monitoring performance metrics.