Top Analytics Jobs in Pittsburgh, PA

Supports analytics product improvements by researching data issues, designing reports, documenting business requirements, developing use cases, and conducting user acceptance testing. The role creates training materials, facilitates user training, supports credit unions and internal users, promotes business intelligence practices, and helps transition analytics solutions into business operations.

Leads marketing and enrollment analytics across acquisition and conversion funnels. Analyzes channel performance, ROI, attribution, forecasting, experimentation, and marketing mix modeling; develops recommendations for budget allocation and performance improvement. Uses Power BI, SQL, Python or R, and institutional and marketing datasets to build models, automate monitoring, identify anomalies, and support cross-functional decisions. Owns marketing measurement standards, data quality, tracking, and analytical roadmap while partnering with Marketing, Enrollment, Field, and Institutional Analytics teams.

Leads CookUnity’s Advanced Analytics function, setting strategy and partnering with Product, Finance, Operations, Marketing, and leadership. The role involves experimentation, causal inference, retention and growth analysis, marketing measurement, product impact evaluation, and translating insights into business decisions. This hands-on player-coach will guide complex analytical work, develop analysts, improve analytical rigor, and shape team structure and priorities.

Supports Somali-speaking learners in a fully virtual data analytics program. Responsibilities include answering questions, facilitating breakout rooms, holding office hours, reviewing materials, grading assignments, providing feedback, recording walkthroughs, monitoring learner progress, and escalating concerns. The role also requires supporting live sessions, communicating in Somali and English, attending onboarding and staff meetings, and submitting weekly progress reports.

Owns the enterprise Snowflake data platform end to end, including architecture, ingestion, transformation, security, governance, reliability, performance, cost optimization, and AI enablement. Establishes engineering standards, reviews architecture, resolves complex production issues, mentors data professionals, and leads cross-functional adoption of scalable, governed analytics capabilities. The role provides senior technical influence without direct people management and supports secure MCP-based AI integrations.

Leads and manages an analytics engineering team while contributing to data transformation, modeling, quality, and delivery solutions. Establishes modeling and development standards, implements analytics engineering tools, supports client engagements, improves reporting and visualization processes, allocates team resources, mentors engineers, supports presales, and drives internal quality and process improvements.

Owns analytical projects across customer onboarding, transaction behavior, and platform operations. Designs dashboards, KPI frameworks, reporting workflows, and data pipelines while delivering actionable insights. Partners with Engineering, Product, Payment Operations, Compliance, and Finance; mentors colleagues; manages project scope and priorities; resolves ambiguity; and drives cross-functional alignment. Requires advanced SQL and data modeling skills, BI tool experience, analytical scripting familiarity, FinTech domain knowledge, and 4+ years of analytics experience.

Build and maintain production data pipelines that transform robot logs and telemetry into reliable, queryable datasets. Design Spark-based ETL workflows, orchestrate processing with Airflow or similar tools, manage gold-layer datasets, and implement data quality, schema evolution, monitoring, and metadata practices. Collaborate with robotics, hardware, reliability, analytics, and ML teams on data modeling, fleet insights, debugging, and root-cause analysis. The role may also contribute to Python, Java, or C++ libraries supporting data capture and consumption.

Leads the design, development, testing, tuning, and optimization of financial crimes detection models across AML, fraud, KYC, and sanctions. Performs statistical analysis, threshold calibration, back-testing, model efficacy assessments, feature engineering, and root cause analysis. Configures financial crimes platforms, monitors model performance, establishes testing and governance standards, and partners with Model Risk Management and leadership on validation, audit, regulatory, and risk-related initiatives.

Own executive reporting and data strategy for autonomous vehicle system performance. Lead the weekly Software Performance Review, develop board-level reporting, analyze robotics and autonomy metrics, translate technical findings into strategic recommendations, and establish data visualization standards. Partner cross-functionally across engineering and performance teams, create data-driven feedback loops, and mentor Business Analytics and Business Intelligence engineers.

Owns DeVry University's website measurement ecosystem, including GA4, GTM instrumentation, event taxonomies, data quality, tracking governance, and conversion measurement. Analyzes SEO, AI search visibility, website journeys, acquisition, engagement, and conversion performance using SQL and dashboarding tools. Investigates anomalies and friction, supports experimentation, automates monitoring, and delivers prioritized recommendations. Partners with web, marketing, SEO, technology, analytics, and external teams to improve measurement reliability, digital experience, and prospective student conversion.

Leads Lumicera’s enterprise data and analytics function, setting strategy, roadmaps, governance, investment priorities, and delivery standards. Manages analytics teams, data products, reporting, dashboards, data platforms, and governed self-service capabilities. Partners with executives and operational, clinical, technology, finance, compliance, and pharmacy stakeholders to translate business priorities into measurable insights. Oversees vendors, budgets, data quality, privacy, metadata, lineage, and AI-readiness while supporting regulated healthcare and specialty pharmacy operations.

Build and support production analytics models using SQL, dbt, BigQuery, Looker, and LookML. Develop governed semantic layers, self-service analytics, automated tests, and reliable datasets for business and AI use cases. Partner with stakeholders to translate ambiguous requirements into reusable solutions, investigate data discrepancies, optimize performance, support platform modernization, and maintain data quality, privacy, and documentation.

Leads enterprise advanced analytics and modeling to identify drivers of business performance across brands, markets, customers, accounts, and geographies. Translates findings into prioritized actions, playbooks, launch strategies, and scenario-based recommendations. Oversees rigorous, scalable analytical approaches, partners with senior stakeholders, and develops analytics talent across the organization.

Builds business-critical dashboards, scorecards, reports, and ad hoc analyses using SQL, Python, Excel, Power BI, and Tableau. Analyzes KPIs, identifies trends and root causes, automates recurring reporting, validates data, and translates complex findings into actionable insights for stakeholders and leadership. The role collaborates with data engineers and cross-functional teams to improve reporting workflows, data pipelines, and decision-making.

Own the architecture and standards for a trustworthy BI analytics platform. Design data models, ingestion and transformation patterns, lineage, PII controls, reliability SLAs, observability, schema governance, and cost management. Partner with engineers, analysts, business leaders, Security, Legal, and Compliance; enforce testing, CI/CD, infrastructure as code, and data quality practices. Mentor data professionals and document architectural decisions.

Owns end-to-end customer analytics workstreams, including KPI frameworks, multi-source dashboards, reporting, data governance, quality assurance, and insight delivery for government digital communications programs. Presents recommendations to stakeholders, mentors junior analysts, leads Agile ceremonies, documents analytics practices, resolves data issues, and evaluates AI-assisted analytics tools.

Analyze startup user and product data, identify trends and drivers, and turn findings into strategic recommendations. The role owns key metrics and dashboards, leads analytical deep dives, sizes opportunities, evaluates product tradeoffs, supports roadmap prioritization, and develops external-facing insights about startups in partnership with marketing and communications.

Manages programmatic analytics and insights for client accounts, leading measurement frameworks, brand lift studies, incrementality testing, and A/B experiments. Develops media and campaign strategies, communicates performance insights to clients, and supports pitches and QBRs. Oversees, mentors, and develops analysts while partnering with Product, Engineering, Sales, and Customer Success teams to improve measurement tools, campaign optimization, and analytical capabilities.

Own campaign measurement and reporting across video, podcasts, newsletters, social, digital, and live events. Build dashboards, benchmarks, partner-facing insight decks, case studies, and renewal materials. Monitor campaign KPIs, coordinate third-party measurement and brand lift studies, and turn audience and performance data into recommendations for pricing, packaging, content, and business growth.

Build and optimize Customer 360 data models, ELT pipelines, semantic layers, and identity resolution frameworks in BigQuery. Develop Tableau dashboards for customer acquisition, retention, churn, product adoption, and deposits. Sync behavioral data with marketing and CRM platforms such as Braze, implement data quality and observability controls, and partner with Marketing, Product, and business leaders to turn customer analytics into growth initiatives.

Design and maintain scalable dbt data models and ELT pipelines in Snowflake; architect reusable data assets, governance, and SaaS metrics; build AI-enabled data foundations and LLM workflows; integrate analytics into operational tools and partner cross-functionally to productionize AI-driven use cases.

Design and maintain scalable dbt data models and ELT pipelines in Snowflake. Architect data foundations to power AI and LLM-enabled workflows, operationalize core SaaS metrics, and build reusable data assets for analytics and activation. Partner cross-functionally to embed analytics into workflows and ensure scalable, secure architecture.

Build and scale secure data lakehouse and warehouse infrastructure supporting analytics, machine learning, clinical AI performance monitoring, and self-service insights. Develop scalable data pipelines, models, orchestration, quality controls, and LLM-enabled analytics tools using heterogeneous clinical and EHR data. Collaborate with engineering, data science, clinical, product, and client success teams to establish trustworthy metrics and technical solutions.

Lead a team delivering product and business analytics for Fetch's commerce and shoppable experiences. Own prioritization, experimentation, measurement, KPI dashboards, and stakeholder-facing insights to inform product, marketing, and commercial decisions. Manage and develop analysts while partnering cross-functionally to ensure data quality, repeatable analyses, and actionable recommendations.