Top Data & Analytics Jobs in Pittsburgh, PA

As a Quantitative Strategist, you'll design pricing tools for investment professionals, develop analytics frameworks, and create scalable data pipelines while collaborating with investors to analyze macro financial products.

The Staff Analytics Engineer will establish a data foundation aiding various teams at Kit by refining reporting models, ensuring consistent metric definitions, and enhancing stakeholder self-service capabilities.

The Senior Data Analyst will support marketing and sales, drive growth through analytics, and collaborate with key stakeholders to enhance data-informed decision making.

Design, develop, and maintain enterprise Power BI dashboards and reports. Integrate data from SQL Server, Azure, Excel and other sources, perform data modeling and DAX calculations, validate data, and document data models and reporting logic while partnering with business stakeholders.

Design, build, and scale data pipelines and integrations for the TDX platform. Implement REST API integrations, ingest and unify customer data, optimize pipelines for performance and quality, ensure data security and governance, and collaborate with Product, Data Science, and customer teams to deliver reliable analytics-ready data.

The Director of Analytics will lead the analytics strategy and operations for a top-grossing mobile app, driving data-driven decision-making and insights.

Lead analytics engineering: architect, build, and maintain scalable data pipelines and dbt models; ensure data is research-ready; partner with Engineering, Data Science, and Commercial teams; implement product analytics and optimize data workflows for scale.

Design and implement credit strategies using data, machine learning, A/B testing and advanced analytics to optimize underwriting, pricing, and credit line decisions. Lead end-to-end analytics for credit card products, monitor portfolio performance, conduct root-cause analysis, partner cross-functionally, and communicate findings to stakeholders.

Lead enterprise Power BI architecture and governance, design scalable semantic models and high-performance reports, enable self-service analytics, optimize large-dataset performance, and mentor analytics teams while aligning solutions with business requirements and data engineering.

Optimize publisher monetization by analyzing bidstream and auction data, building monitoring/alerting systems, running A/B tests, performing root-cause analyses, and producing actionable insights for cross-functional teams to maximize yield and revenue.