Collaborate with cross-functional teams to understand business requirements and identify opportunities for AI integration in generative chatbot solutions. Analyze large datasets to extract meaningful insights, patterns, and trends to drive the development and enhancement of generative AI chatbots. Design, develop, and maintain scalable data pipelines to support AI model training and real-time analytics.

Drive NLP and machine learning projects and be responsible for developing methodology and solutions to support technical, analytical, and operational requirements. Design and implement machine learning algorithms for NLP/LLMs or deep learning models at scale to meet business requirements.

As a Principal AI Engineer, you will design, develop, and deploy AI solutions that address complex business challenges. This role requires advanced expertise in artificial intelligence, including machine learning and natural language processing, and the ability to implement these technologies in production-grade systems.

LivePerson is hiring a BI Analyst II on the Ops Excellence team to transform data into actionable insights that drive revenue growth and strategic business decisions. The role involves developing and optimizing BI dashboards, using SQL for data extraction and analysis, and collaborating with cross-functional teams to ensure data accuracy and consistency.

Design, build, and test custom data warehouse and BI solutions for Myers-Holum clients using the Oracle NetSuite Analytics Warehouse (NSAW) platform. Translate business requirements into technical specifications and develop custom data integration solutions to ingest data from multiple sources.

This role involves hands-on design, development, deployment, and maintenance of integration processes between applications using Oracle Integration Cloud (OIC), Dell Boomi, or other data integration/pipelining tools. The Senior Developer will develop custom data integration solutions and data warehouse solutions, integrate with REST APIs, and collaborate with cross-functional teams.

Work closely with Product Insurance to build, improve and implement data ETLs and analysis. Apply statistical and machine learning techniques on large datasets. Evaluate the utility of non-traditional data sources.