Top Data Science Jobs in Salt Lake City, UT

The role involves leading pricing experimentation, developing pricing models, analyzing data, and collaborating with stakeholders to optimize pricing strategy.

The AI Data Specialist manages AI data solutions, supports analytics, collaborates with teams to meet client requirements, and drives data innovation.

The internship involves enhancing Power BI visualizations, integrating additional data sources, creating documentation, and training staff on the updated platform.

Lead data science initiatives by developing machine learning models, conducting data analysis, collaborating with teams, and mentoring junior data scientists to drive strategy and insights.

The Senior Data Engineer will develop data pipelines, maintain data infrastructure, and collaborate on data modeling and management. Responsibilities include implementing cloud-native solutions and monitoring data workflows while fostering team collaboration and personal growth.

The Data Scientist III will develop AI models for digital pathology, analyze data, collaborate with teams, and communicate findings. Requires a PhD and 5+ years experience.

The Data Scientist II (RWD) will analyze real-world insurance claims and EHR data, conduct statistical analysis, and develop AI models while collaborating with experts to produce insights and communicate findings.

The Data Scientist II will develop AI models for digital pathology, evaluate outcomes, collaborate on clinical requirements, and communicate findings effectively.

The Senior Data Scientist will optimize the Places app's recommendations using data analysis, A/B testing, and collaboration with cross-functional teams.

As a Senior Data Visualization Engineer, you will create data visualizations, collaborate with teams to build reporting solutions, and translate business goals into actionable insights.

This role focuses on developing and maintaining statistical models for pricing and underwriting in the insurance industry, while collaborating with teams and educating partners on model use.

Lead the development of causal models for pricing and marketing strategies, enhancing understanding of customer lifetime value while collaborating with cross-functional teams.