Top Machine Learning Jobs in Tulsa, OK

As a Risk Manager, you'll analyze and mitigate security risks, implement fraud defenses, and collaborate with cross-functional teams to enhance security objectives.

As a Machine Learning Engineer, you'll enhance ML productivity, improve model deployment, and implement algorithms for credit decisioning systems.

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

Join Clarity AI's Talent Community by submitting an open application for various roles in product, technology, finance, marketing, or operations to drive positive impact.

The Assistant Modeling Manager develops and enhances auto insurance rating plans, applying advanced modeling techniques and collaborating with data scientists to provide insights and ensure compliance with regulations.

The Credit Analyst will develop credit risk strategies, manage decision strategies, analyze credit trends, and collaborate with multiple teams to ensure compliance and profitability in credit processes.

The role involves driving data governance strategy and practices across the Bank, collaborating with cross-functional teams, leading data quality initiatives, and mentoring analysts while ensuring compliance with data governance standards and improving data quality.

As a P&C Actuary, you will assess risks for insurers, support audit teams, and maintain compliance with regulations, while growing client relationships and improving tools for efficiency.

The Lead Analyst will drive data strategy, manage analytics projects, partner with cross-functional teams, and enhance data-driven decision-making through insights.

In this leadership role, the Principal Architect develops and implements enterprise-wide data security strategies, focusing on AI and ML challenges, while mentoring teams.

Develop and productionize a next-gen Dispatch System, build predictive models, automate processes, and lead a small team in optimizing operations.

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

The Business Analyst 2 analyzes AI-powered data solutions, optimizes customer experience automation, and collaborates with teams to drive business insights and value.

The Data Analyst will analyze and transform complex datasets into actionable insights, supporting federal healthcare decision-making and ensuring data quality.

The Staff Analytics Engineer builds data workflows, ensures data integrity, resolves customer issues, and develops insights products, leveraging SQL and Python skills.

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

This role involves training AI models in Energy and Power by providing feedback on outputs, problem-solving, and identifying biases in the AI's knowledge base.

As an AI Tutor, you will teach, evaluate, and red-team AI models in data science principles, focusing on statistical modeling, machine learning, and data ethics.

The Data Engineer will design and maintain ETL pipelines and data storage solutions, collaborating with cross-functional teams to ensure efficient data processing and delivery.

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 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.

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

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

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

Lead ML research and development, collaborating with engineers and clinicians to create enterprise-grade products and establish a research agenda while sharing insights through publications and presentations.