Top Machine Learning Jobs in Dallas, TX

This role involves applying advanced data science and machine learning methods to healthcare data, leading teams, managing client relations, and developing analytics products for payers, while mentoring junior staff.

The role involves designing and implementing advanced analytics solutions for healthcare payers, analyzing complex problems, mentoring juniors, and building client relationships.

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.

Lead design, enhancement, and maintenance of the bank's data warehouse and analytical platforms. Drive data engineering best practices, support ML/predictive capabilities, manage production issues, automate processes, collaborate on feature design, and mentor engineering teams while partnering with PMO on Agile delivery.

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.

Lead marketing analytics, predictive modeling, experimentation, and measurement. Build segmentation, personalization, attribution and MMM frameworks; partner with marketing, data engineering, and IT to operationalize models and deliver executive reporting and optimization.

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.

The Senior Actuarial Predictive Modeler develops predictive models for pricing and lifetime value, collaborates with teams, ensures compliance, and leads projects.

Lead and build an end-to-end data testing and quality assurance function, driving data governance adoption, automation and AI-enabled testing, stakeholder alignment, metrics reporting, and remediation across divisions while managing a team in Dallas.

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.

The Marketing Data Scientist will apply advanced analytics and machine learning to drive marketing strategies, focusing on connecting digital engagement to physical outcomes. Responsibilities include experimentation, reporting, predictive modeling, and collaboration with stakeholders for business insights.