Top Remote Senior Level Data & Analytics Jobs

The Senior Data Engineer will develop and maintain ETL/ELT pipelines, analyze and model complex data, and collaborate across teams to optimize data solutions for performance and scalability. Responsibilities include working with technologies like SQL, Python, and AWS, and ensuring data privacy and security in architectures.

The Senior Data Engineer will design, maintain, and enhance the company's data analytics pipeline, focusing on data warehouse and ETL processes. Responsibilities include developing tools for monitoring data health, collaborating with stakeholders, and ensuring data accuracy and reliability.

As a Staff Machine Learning Engineer at Handshake, you will lead a small team to enhance AI products and infrastructure, focusing on Generative AI and Recommendations. You will develop machine learning systems, design partnerships across teams, and drive technical direction while ensuring high-quality execution and user-centered solutions.

As a Senior Data Scientist, you will leverage advanced analytics tools to develop data-driven solutions and lead end-to-end data science projects. Responsibilities include building predictive models, applying statistical methods, collaborating with teams, and delivering actionable recommendations to stakeholders, while staying updated on emerging Microsoft technologies.

The role involves performing high-quality legal and corporate research, responding to research requests, synthesizing results, and providing findings in a clear manner. The position requires collaboration with other researchers and excellent customer service skills to support attorneys and staff.

As a Senior Data Engineer at Clear Capital, you will design and develop data movement applications using AWS services, build data pipelines, implement a data governance strategy, and collaborate with cross-functional teams in an Agile environment.

As a Data Scientist at Pacaso, you will analyze data to provide insights, collaborate with various teams, and support advanced analytics initiatives. Responsibilities include data cleansing, defining performance metrics, communicating findings, and building models to understand customer growth.