Data Scientist, AI Development
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Key details
- Location
- Omaha, NE, United States
- Work style
- Onsite
- Function
- Data & ML
- Focus area
- AI / ML
- Posted
- 13h ago
Skills
ai agentsfund administrationgenerative aillmmachine learning
About the role
About the team
Ultimus is investing in AI to transform how fund administration work gets done, from generative AI assistants, intelligent document processing and machine learning to a growing set of agentic AI workflows. Our AI Development teams are small, cross-functional groups of AI engineers, data scientists, data engineers and AI analysts who partner closely with our operations experts to redesign key workflows and build the AI solutions that support them, with AI agents an increasingly important part of that work. They are backed by a dedicated AI Infrastructure team and a shared enterprise AI platform.
About the role
As Data Scientist in an AI Development pod you design the AI approach for each workflow and prove that it works. You shape the models, prompts and agent logic, and you own how we measure accuracy, quality and savings.
What you'll do
Work with operations experts to break a workflow into steps and decide where AI models, AI agents, rules or people should handle each one.
Design the right AI approach for each task, whether predictive models, LLM prompts and retrieval, or agent reasoning, and select the right models.
Build evaluation sets and metrics (accuracy, exception rates, review time) and run offline and online evaluations before and during pilots.
Analyze pilot results, find failure patterns and improve the solutions until they meet the targets to go live.
Measure the time and cost saved by each workflow and report results to the program team.
Package what works into reusable patterns for the next workflow.
Ultimus is investing in AI to transform how fund administration work gets done, from generative AI assistants, intelligent document processing and machine learning to a growing set of agentic AI workflows. Our AI Development teams are small, cross-functional groups of AI engineers, data scientists, data engineers and AI analysts who partner closely with our operations experts to redesign key workflows and build the AI solutions that support them, with AI agents an increasingly important part of that work. They are backed by a dedicated AI Infrastructure team and a shared enterprise AI platform.
About the role
As Data Scientist in an AI Development pod you design the AI approach for each workflow and prove that it works. You shape the models, prompts and agent logic, and you own how we measure accuracy, quality and savings.
What you'll do
Work with operations experts to break a workflow into steps and decide where AI models, AI agents, rules or people should handle each one.
Design the right AI approach for each task, whether predictive models, LLM prompts and retrieval, or agent reasoning, and select the right models.
Build evaluation sets and metrics (accuracy, exception rates, review time) and run offline and online evaluations before and during pilots.
Analyze pilot results, find failure patterns and improve the solutions until they meet the targets to go live.
Measure the time and cost saved by each workflow and report results to the program team.
Package what works into reusable patterns for the next workflow.