Top Machine Learning Jobs in Dallas, TX

Leverage advanced analytics, data manipulation, visualization, statistical modeling, predictive analytics, and machine learning to generate client insights and recommendations. Apply Adobe Experience Cloud solutions to support business transformation and strategic decision-making. Build client relationships, manage and inspire teams, navigate complex engagements, uphold professional standards, and deliver quality outcomes while developing technical and consulting expertise.

Leads data analysis and advanced analytics workstreams for clients, using statistical modeling, machine learning, data visualization, and Adobe Experience Cloud technologies to improve operations and strategic decision-making. Manages project planning, budgeting, execution, and completion while mentoring teams, maintaining data integrity and security, building Tableau and Power BI dashboards, identifying business opportunities, and integrating innovative analytics practices.

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.

Lead architecture for data, reporting, and analytics product family: set target-state designs, guide technology evaluation and AI-enabled integrations, produce and review production code, enforce governance, resiliency, security, and auditability, and provide technical leadership across teams and vendors.

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.

Build predictive data pipelines, machine learning models, dashboards, and automated decision tools for portfolio strategy. Analyze product performance, costs, monetization, competitive intelligence, customer behavior, and feature opportunities. Govern metrics and data quality using SQL while enabling self-service AI and natural-language data access. Support roadmap prioritization, ROI assessment, initiative tracking, and executive decision-making through advanced analytics and financial modeling.

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.

Design, build, and maintain large-scale data infrastructure and pipelines (data lakes/warehouses). Integrate diverse data sources, optimize processing and queries, enforce data quality and security, implement monitoring/alerting, troubleshoot issues, and collaborate with cross-functional teams while exploring new data frameworks and cloud services.

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 strategy and execution to prevent, detect, and disrupt digital fraud, scams, and money mule activity. Build and mentor data science and analytics teams, develop ML predictive models, partner with product, cyber, vendors, and risk teams, and drive prevention-first controls, compliance, and operational efficiencies across payments, onboarding, and authentication channels.

Entry-level Associate Data Analyst supporting analytics, data science, data engineering, and project management rotations. Deliver insights, build dashboards, automate reporting, partner with stakeholders, and apply ML/LLM tools to drive product and client analytics.

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.

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.