Top Remote Senior Level Data Science Jobs

As a Data Science TLM Manager, you will shape Airbnb's search and personalization strategy by leading a team of data scientists, developing specialized models for the recommendation platform, and ensuring collaboration between the relevance team and product organization to enhance user experience.

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.

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.

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.

As a Data Scientist at Airtable, you will partner with product teams to drive insights and identify business opportunities, manage experiments, build a data culture, and communicate findings through storytelling and visualizations.

The Sr. Data Scientist will leverage analytics and machine learning to inform product development, optimize user experiences, and drive key performance metrics. Responsibilities include conducting experiments, analyzing customer usage, developing reporting, and presenting findings to influence data-driven decisions.