Top Remote Machine Learning Jobs in Tulsa, OK

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.

The Senior Data Scientist will optimize product performance, drive product innovation through data-driven insights, and foster a culture of data-driven decision-making across teams.

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

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

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

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.

The Machine Learning Architect will design and implement ML solutions on cloud platforms, working directly with customers to align strategies with business goals. Responsibilities include end-to-end project management, model deployment, and maintaining strong customer relationships.

The Marketing Analyst develops data visualizations and executive dashboards, utilizes machine learning for customer insights, and collaborates with teams to drive strategic decisions.

The role involves developing quantitative modeling solutions to assess risks, collaborating with various departments, and effectively communicating insights through data visualization.

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

Lead the fraud strategy to protect customers and card portfolios, develop real-time models with Data Science, and manage fraud performance metrics. Collaborate across teams to implement effective fraud controls and optimize processes.

The Clinical Informatics Lead oversees data annotation and informatics teams, ensuring data quality, compliance, and collaboration with clinical standards for healthcare solutions.

Manage and optimize GPU capacity and compute resources, develop data models and reporting systems, collaborate across teams to improve efficiency and meet business needs.

The role involves developing predictive models for catastrophe risk using advanced analytics, machine learning, and statistical techniques. Responsibilities include analyzing large datasets and collaborating on financial risk modeling to enhance accuracy. The individual will document processes and ensure consistent modeling methodologies are upheld.

Analyze content performance, influence product roadmap, manage content strategies, classify data, and collaborate with engineering on AI and ML initiatives.

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

Lead a data science and analytics team for Netflix's game product and platform. Responsible for measurement, experimentation strategies, and coaching the team to deliver insights vital for games strategy.

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.

The Director of Digital Business Innovation will lead digital transformation initiatives, emphasizing data, AI, and ML to enhance operational efficiency and business innovation. Collaborate with various teams to execute strategies and drive business results.