Top Machine Learning Jobs in Pittsburgh, PA

Lead the development and implementation of automation techniques using AI and machine learning to improve life underwriting operations and processes.

Lead deep-dive analyses into account takeover and fraud, design and implement real-time defenses, collaborate with product/engineering/data science, run incident response, and deliver actionable insights to protect users while preserving UX and core metrics.

The Risk Analyst will develop strategies to mitigate fraud risk, analyze data, and collaborate with various teams to support low friction customer experiences. Responsibilities include reviewing accounts, creating analytical models, and reporting on progress against business goals.

As a Senior Data Scientist, you will analyze data, build models, and collaborate with teams to enhance credit evaluation using machine learning.

Lead the ML Data Enablement team to define strategy and execution for accelerating third-party and internal data onboarding, enforce data quality and SLAs, build metadata and lineage standards, and deliver scalable data infrastructure and workflows to reduce time-to-production for ML models.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

The Principal, Advanced Analytics - Subscriber Forecasting leads forecasting methodologies and develops frameworks for subscriber volume forecasting, integrating advanced analytics, time-series modeling, and AI. Responsibilities include scenario planning and cross-functional collaboration to inform enterprise decision-making.

Design, build, and maintain forecasting and portfolio optimization models for U.S. power markets; analyze market outcomes, track supply/demand/congestion dynamics, and apply statistical, optimization, and ML methods to inform commercial decisions.

Lead content programming through analysis, classification, and editorial judgment. Monitor performance, synthesize query analysis, propose product improvements, curate content, and collaborate with Engineering/Data Science on LLM/ML/NLP initiatives.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

The Manager, Growth Analytics & Marketing Science will build and evolve marketing measurement frameworks, drive analytics, and optimize marketing strategies through data and AI.

Lead RWE study design and execution: develop protocols, statistical analysis plans, and R/SQL programs to produce analysis-ready datasets, tables, and figures; apply causal inference, time-to-event, and predictive methods; collaborate with scientists and stakeholders to deliver RWE insights.

The Lead Quantitative Analytics Associate conducts statistical analyses and builds predictive models, responding to business needs and enhancing existing models. They work with large datasets, ensuring data management and model maintenance, while communicating insights effectively within the organization.

Join Nextdoor's machine learning team to build data-intensive products, develop ML models, analyze datasets, and enhance user experiences. Collaborate closely with product and data science teams.

Lead development and execution of data-driven audit strategies for insurance and PBM clients. Analyze large datasets, design analytics solutions, create dashboards, perform statistical profiling and sampling, ensure regulatory compliance, manage project budgets and client communications, and coach junior staff to improve examination efficiency and effectiveness.

Lead data acquisition and management strategies for AI models, analyze data systems, oversee partnerships, and guide a team in optimized data usage.

Lead the Data & Analytics team, focusing on building data platforms, improving delivery speeds, and integrating Generative AI into data strategies.

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

Drive measurement, causal inference, and experimentation to optimize content promotion and personalization. Build robust metrics, partner with product and engineering, surface discovery opportunities, and independently deliver high-impact analytics and ML solutions.

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.

Build and maintain dashboards and reports (Excel, Tableau, Sigma) by pulling and modeling production data (SQL, Python). Create pricing models for RFPs, define operational and financial metrics, optimize queries and data structures, run A/B experiment analyses, and partner with business leaders to generate insights and recommendations to improve roadside assistance operations and performance.

The AI Data Specialist will perform data-related tasks like collection, evaluation, and annotation to improve AI-generated content.

Design and manage curated fact and dimension datasets, semantic/subject-area models, and governance. Partner with BI and data engineering to enable self-service analytics, ensure data quality and documentation, and prepare datasets to support future ML and advanced analytics.

As an Associate Engineer in Data Science, you will leverage data analysis and machine learning to solve complex problems and develop inspiring digital products.

The Sr. FWA Data Analyst analyzes healthcare datasets for fraud detection using SQL, collaborates with product teams, and engages stakeholders, while presenting findings.