Top Remote Senior Level Data & Analytics Jobs in Phoenix, AZ

The Senior Data Analytics Engineer will build and maintain data pipelines, define reusable data sets for various business functions, and design frameworks to validate data consistency. Responsibilities include ensuring user privacy and security while leveraging the latest tools for data optimization and delivery.

The Senior Scientist in Quantum Applications Chemistry will develop quantum chemistry algorithms, collaborate on hybrid quantum workflows, and engage with clients to solve complex problems using IonQ's quantum computers. This role requires strong expertise in computational chemistry and programming, as well as the ability to communicate technical concepts effectively.

The Senior Staff Scientist at IonQ will lead the development of quantum AI solutions, conduct research to discover new algorithms, and optimize hybrid applications on quantum computers. The role involves collaboration with PhD scientists and various teams while shaping long-term strategies for quantum AI application deployment.

The Senior Analyst will deliver financial insights and analyses for the Go-To-Market function, supporting strategic decision-making and collaboration across teams. Responsibilities include developing financial models using SQL, producing forecasts, and presenting actionable insights to leadership while analyzing performance for continuous improvement.

As a Senior Manager at Arity, you will lead R&D teams in developing machine learning models for driver behavior detection. Your role will involve collaborating with product and engineering teams, managing diverse teams of data scientists, and executing communication strategies to ensure successful project outcomes.

The Data Science Director for Product Analytics will lead a team of data scientists and engineers to develop product-related metrics and insights, deliver self-service analytics, and support reporting efforts for executives. Additional responsibilities include building analytics infrastructure and promoting effective data usage across the company.

The Data Engineer is responsible for designing, implementing, and maintaining the data infrastructure to support business intelligence and analytics. Key tasks include developing scalable ETL/ELT pipelines, optimizing data workflows, and ensuring data quality while collaborating with cross-functional teams.

The Data Engineering Manager will lead a team of data engineers to develop and maintain optimal data pipeline architecture, build data systems for ML and AI models, and work cross-functionally with data scientists. Responsibilities include managing daily operations, extracting and processing client data, and creating the infrastructure for data extraction and loading using SQL and AWS technologies.