Top Remote Senior Level Data & Analytics Jobs

The Senior Data Scientist will analyze complex data, build and deploy machine learning models, write Python code for data analysis, collaborate with teams, and provide feedback on data analyses. They will work in a remote, collaborative culture focused on delivering insights and product improvements.

The Senior Field Application Scientist will manage customer application needs for genomic analysis, train customers on new processes, provide troubleshooting support, develop workflows, and represent the company at customer sites and scientific conferences.

Looking for a Sr. Data Scientist to design, build, and train algorithms and models for large enterprise customers. Responsibilities include collaborating with stakeholders, data manipulation, authoring reports, engaging with development teams, and driving thought leadership. Qualifications require an advanced degree or exceptional ability in a relevant field, 3-5+ years of hands-on experience, knowledge in mathematics and machine learning, and strong computer science fundamentals.

As a Revenue Cycle Analyst, you will analyze large datasets to identify trends and improve the revenue cycle process. You will work on denied claims, track revenue cycle performance metrics, and provide data-driven insights to enhance efficiency and reimbursement. You will also conduct ad hoc data analyses to support decision-making and process changes.

The Financial Systems and Data Analytics Lead will design, implement, and maintain systems for financial data analytics and process automation, collaborating with cross-functional teams to automate accounting entries, support month-end close, and create financial reports, while also engaging in data management and ad-hoc analytics projects.

As a Data Scientist at ShyftLabs, you will analyze datasets, develop simulations, and design experiments to provide actionable insights for improving a complex ML bidding system. Your role involves collaborating with stakeholders and utilizing statistical techniques to drive data-driven decisions.

The Principal Data Engineer will lead the design and implementation of modern data processing platforms, develop scalable data solutions, and collaborate across teams to optimize data pipelines. They will mentor the data engineering team and create tools that drive innovation and operational excellence, focusing on the healthcare sector.