Top Data Science Jobs

The Senior Data Scientist, Data Products role involves leveraging data to enhance product creation and strategy through collaboration, automated systems, quality metrics, and ad-hoc analysis. Responsibilities include creating insights and applying the latest technology trends while leading projects independently.

The Senior Scientist will develop quantum chemistry algorithms, collaborating with cross-functional teams to create optimized quantum workflows and address real-world problems using IonQ's quantum computers, while building reusable software platforms.

The Data Science Manager at Garner will develop care navigation algorithms and analytics, while leading a team of 4-6 data scientists and analysts. Responsibilities include managing projects within the Data Science Guild and contributing to the healthcare mission by driving data-driven insights.

As a Senior Data Scientist at Pie, you will develop best-in-class AI/ML solutions for commercial insurance, focusing on pricing, underwriting, and claims models. Collaborating with multiple teams, you'll enhance data-driven decision-making, conduct model diagnostics, and support deployment and automation of scalable ML pipelines that meet real business challenges.

In this role, you'll lead analytical initiatives by employing techniques like machine learning and optimization to address business problems. Responsibilities include managing risks, developing reports and dashboards, collaborating across departments, and delivering presentations on findings to various leadership levels.

The Senior Data Scientist in Marketing Analytics will collaborate with the Marketing team to enhance the ROI of marketing initiatives through statistical modeling, machine learning, and data mining. Responsibilities include leading Media Mix Models, establishing marketing measurement frameworks, performing in-depth marketing performance analyses, and developing dashboards to communicate insights.

The Data Scientist at Caterpillar Inc. will perform data analysis to support business decisions, develop statistical models, implement machine learning techniques, and create data visualizations. Responsibilities include optimizing data models, conducting data mining, and leading data analysis projects for product development initiatives.