Data Analyst (Machine Learning and Generative AI)

Kforce has a client in Westlake, TX that is seeking a Data Analyst (Machine Learning and Generative AI).

• Financial services industry knowledge and experience is highly desirable, investment management and/or wealth management domain knowledge a plus
• Strong experience working with data in support of analytics and reporting use cases
• Hands-on experience with relational databases and SQL for analysis, profiling, and data validation
• Understanding of data modeling concepts (e.g., star and snowflake schemas, dimensions and facts) and how they support BI/reporting
• Experience defining or supporting BI/reporting solutions (e.g., Power BI, Tableau, or similar), including KPIs, drill-downs, and filters.
• Experience working with or around ML/LLM solutions (or strong interest and aptitude to learn), including helping to define data requirements, success criteria, and basic monitoring/adoption needs for models and AI-driven reports, in partnership with ML Engineers
• Excellent written and verbal communication skills
• Strong analytical and problem-solving skills with the ability to reason about complex systems and data flows
• Able to understand the technology and software architecture of an application
• Experience with various tools that assist in analysis and testing including SQL Developer, Insomnia, Kafka - Offset Explorer, and Datadog for data validation and debugging, Jira and Confluence
• Willingness to dive in and understand code for analysis and support purposes
• Familiarity with modern AI tools and their application in analysis (e.g., using LLMs to support impact analysis, documentation, testing, or incident diagnostics) is desirable
• Has worked in an Agile environment that uses the Scrum Methodology and is experienced with the related events and artifacts
• Has effectively worked in a global, team-based environment with team members in various locations and countries
• Demonstrated ability to work across business, BI, ML, Data Ops, and Architecture teams to align on standards, data contracts, SLAs, and shared operating mechanisms