Top Remote Senior Level Data & Analytics Jobs in Washington DC,

As the Senior UX and Analytics Lead, you will enhance user experience for Risk Ripple Analytics by producing design deliverables, analyzing engagement metrics, and optimizing user satisfaction. You'll leverage data insights to improve design strategies and collaborate with stakeholders to align business and user needs, driving product adoption and engagement.

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 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.

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.