Top Data Science Jobs in Louisville, KY

As a Staff Data Scientist, you'll analyze complex datasets, guide product strategies with insights, and enhance data infrastructure reliability.

As a Principal Data Engineer, you will define architectural solutions for clients, design data platforms, and mentor junior team members while proposing end-to-end solutions for data management issues.

The Data Scientist II estimates, develops, and implements consumer credit models related to mortgage metrics and utilizes statistical methods and machine learning. This role involves cloud computing, data analysis, and communication of findings to nontechnical teams.

The Senior Staff Data Scientist will lead AI/ML initiatives, developing algorithms for business insights, collaborating across functions, and implementing advanced methodologies in forecasting and optimization.

The Staff Data Scientist will develop models for balancing patient demand and Registered Dietitian supply, optimize staffing and scheduling, and collaborate with multiple teams for data-driven decision making.

As a Data Scientist, you'll design and develop reports, collaborate on complex problems, and employ machine learning techniques to drive insights for clients.

As a Senior Data Scientist, you'll develop and deploy machine learning solutions for advertising measurement products, collaborating with various teams to enhance capabilities and performance.

Lead and manage a team of data scientists to leverage insights for business growth, influence decision-making, and foster an inclusive team culture.

The Senior Data Scientist will own investigation and analytics to combat blockchain fraud, developing models and visualizations for law enforcement agencies. Responsibilities include collaborating with engineers, staying updated on blockchain developments, and establishing best practices for data-driven decision-making.

As an Optimization Scientist, you will leverage AI and mathematical modeling to develop and deploy optimization models in collaboration with interdisciplinary teams, ensuring efficiency and scalability for real-world problems.