Top Machine Learning Jobs in Dallas, TX

Lead data ownership and governance for wholesale credit risk. Define data strategies, ensure data quality, metadata and lineage, enable data products, mitigate data risks, and coordinate cross-functional delivery for analytics and reporting.

Lead and develop a team delivering data conversion for customer implementations. Drive adoption of AI and automation, manage complex/at-risk migrations, track KPIs, and improve processes through experimentation and transformation.

Implement, install and administer an advanced analytics platform and workspaces (SAS, Tableau, R, ML). Ensure IT policy compliance and service levels, support connectivity to data sources (Hadoop, Oracle, SQL Server), perform capacity planning, performance tuning, document procedures, troubleshoot issues, coordinate implementation with architects and service providers, and automate platform administration with scripting.

The AI Data Specialist builds and maintains data pipelines, models, and integrations for AI systems, working closely with clients to ensure data quality and effective communication. They manage end-to-end data delivery for multiple projects in a fast-paced environment, translating complex problems into clear solutions.

Lead complex analytics projects supporting client experience transformation: gather and validate structured and unstructured data, apply advanced analytics and machine learning, produce executive visualizations and recommendations, manage recurring reporting, enforce data quality standards, and mentor other analysts to drive business decisions and improve client outcomes.

Lead end-to-end analytics for Flagship Client and Distribution: partner with stakeholders to frame problems, perform advanced analyses and machine learning, ensure data quality, develop recurring analytics products and executive visualizations, and mentor analysts to drive data-driven decisions.

Manage end-to-end catastrophe modeling projects, support client discussions on reinsurance strategy and portfolio management, maintain stakeholder relationships, develop region/peril expertise, perform data management and technical analysis, and lead internal research and automation initiatives.

Join Oliver Wyman's Data & Analytics team to design and implement analytics and ML solutions, build prototypes, communicate results to clients, and support projects across industries including finance, energy, retail, and transportation.

Design, develop, and maintain ETL pipelines, databases, and data visualizations to support 300mm semiconductor manufacturing. Analyze operational performance, automate data extraction, troubleshoot systems, collaborate with stakeholders, and integrate emerging technologies to improve manufacturing efficiency.

Lead design, implementation, and scaling of enterprise Palantir data solutions. Oversee cross-functional teams to build data pipelines, integrations, governance, and advanced analytics (ML/AI). Manage project delivery, stakeholder engagement, performance optimization, and mentor senior engineers and analysts while ensuring security and regulatory compliance.

Lead development, validation, and operationalization of P&C actuarial models and workflows. Convert actuarial requirements into production-ready code, leverage cloud/AI tools, validate data pipelines, produce client-ready reporting, and liaise between actuarial SMEs and engineering teams while contributing to practice tooling and business development.