Top Machine Learning Jobs in Phoenix, AZ

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

As a Senior Data Scientist, you will leverage machine learning and statistical techniques to solve complex business problems and drive product innovations. You will collaborate with cross-functional teams and analyze data to help shape product strategies and decisions.

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

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 Data Analyst will prepare and analyze data for predictive modeling, support multiple projects, and collaborate with various teams to enhance data processes and insights.

As Director of Data Science, you will lead predictive solutions and analytics for marketing, sales, and product development, mentor teams, and establish data-driven strategies aligned with business objectives.

Lead the evaluation and optimization of large-scale datasets for AI training, ensuring data quality and collaborating with research teams.

The role involves data-related tasks like data collection, evaluation, annotation, and object tagging across various content types.

SirenOpt is looking for individuals interested in potential future opportunities. Interested candidates can submit their resumes for consideration.

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 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.

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 Global Strategic Feasibility Analytics Lead develops feasibility data analytics initiatives, transforms data into insights, collaborates with stakeholders, and drives data-driven decision-making for study planning.

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

The Machine Learning Engineer develops AI solutions for cancer care using expertise in ML algorithms and genomic data, collaborating across teams.

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.

As a Machine Learning Engineer, you'll develop and deploy ML models for medical imaging, collaborate with teams, and optimize for production environments.

As an ML Engineer, you will build and productionize predictive models for ad inventory and campaign performance, contributing to the growth of Netflix's ad platform.

As a Senior Data Scientist, you will develop models to extract insights from complex datasets, focusing on temporal and geospatial features, while collaborating with engineering teams to implement solutions.

As a Senior Geospatial Machine Learning Engineer, you will develop and improve algorithms for vegetation analysis, enhance existing products, and lead projects impacting wildfire risk management.

Design and implement machine learning models to improve Risk and Fraud detection systems. Lead technical strategy and partner with operations to address rapidly evolving challenges.