Top Artificial Intelligence Data & Analytics Jobs in Nashville, TN

The Revenue Analytics Manager will analyze customer success and partner analytics, delivering insights to drive retention and revenue growth, working cross functionally with leadership and data teams.

As a Staff Product Analyst, you'll define analytics strategies, build measurement infrastructure, design experiments, and partner with product teams to boost self-serve conversion and product adoption.

As a Senior Data Scientist, you will analyze data, build models, and collaborate with teams to enhance credit evaluation using machine learning.

As a Data Engineer II, you will build and optimize data pipelines in Databricks, ensure high-quality data delivery, and support generative AI applications. You will collaborate with data scientists and AI engineers to provide reliable data infrastructures and meet business needs.

The Analyst, Transaction Monitoring role involves reviewing transaction alerts, conducting investigations on fraud and compliance, documenting findings, and optimizing operational processes.

Lead analytics implementations using Google Analytics and Tag Manager for clients, providing mentorship and managing projects with a focus on enhancing clients' digital strategies.

The Data Modeler will compile and organize folder properties, process feedback, and utilize Symantec Vontu and DLP expertise.

As a Principal Data Architect, you'll lead AI-native data transformations using GCP, design AI architectures, modernize legacy systems, and collaborate with clients.

Implement and deliver Microsoft-based data solutions: gather requirements, build ETL pipelines, perform dimensional modeling, develop complex transformations (SQL, Python, DAX), and create Power BI reports while mentoring teammates and supporting client engagements.

The Azure Data Engineer will work with Azure Cost Management, advising on billing strategies, and managing large datasets for FinOps and analytics.

The Senior Quantitative Analyst is responsible for building data pipelines, conducting Monte Carlo simulations, and converting complex Excel models to code while communicating effectively with stakeholders.