Top Senior Machine Learning Jobs in Pittsburgh, PA

The Senior Manager, Economic & Industry Insights, analyzes large datasets to generate actionable insights in the automotive sector, influences strategic decisions, and engages with stakeholders through published reports and presentations.

The MDM Architect will lead technical architecture and design for Product Master Data Management, ensuring integration and delivery of data solutions across multiple platforms and teams.

As a Principal Data Analyst, you'll leverage machine learning and AI to improve outcomes, manage large data sets, and guide analytics modelers for effective data solutions.

Lead marketing data science efforts, overseeing analytics and machine learning strategies to enhance user acquisition, engagement, and retention. Mentor a team and communicate data insights to executives to influence marketing and budget decisions.

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.

The Manager of RevOps/Yield analyzes patterns and data to optimize ad operations, manage vendor relationships, and oversee a remote team for revenue generation.

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.

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.

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.

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

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.

Drive GTM analytics for Marketing and Sales by building multi-touch attribution, improving funnel conversion, maintaining reliable BI dashboards, automating reporting with AI, and delivering actionable revenue insights to optimize spend and pipeline health.

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.

Seeking a leader for the MLIR team at Netflix to drive machine learning innovations, collaborate with various teams, and enhance organizational capabilities.

Lead and inspire a team of Machine Learning Scientists and Data Scientists at Netflix, focusing on the ads business and media planning. Enhance partnerships, drive success through collaborative projects, and ensure high-quality outputs that align with business goals.

Lead a data science team to drive consumer acquisition strategies and improve Netflix's signup processes through analytics, experimentation, and machine learning.

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.

As an ML Engineer, you will build and productionize predictive models for ad inventory and campaign performance, contributing to the growth of Netflix's ad platform.