Contribute to the development of GenAI solutions, including prompt engineering, retrieval-augmented generation (RAG), fine-tuning, AI agents, and multi-agent systems (MAS)
Apply econometric modeling techniques such as generalized linear models (GLMs), time series analysis, and semi-parametric models (e.g., fractional response models)
During the development, validation, and monitoring of models, verify compliance with model-related regulatory requirements and standards
Enforce DevOps best practices, including version control (Git), CI/CD, test automation, infrastructure as code, and system monitoring in the development and deployment of AI solutions
Design, develop, and deploy AI models in real-world client and business environments
Monitor and research emerging AI trends, fostering an agile, forward-looking development environment
Support project delivery and work with clients to process structured and unstructured data to improve business processes, workflows, and decision-making
Support the documentation and technical analysis efforts for validators, auditors, and regulators; clearly communicate complex concepts to non-technical stakeholders
Work with cross-functional teams, data engineers, architects, and data scientists to deliver efficient, high-quality solutions aligned with client needs

Bachelor's Degree
At least 1 year of AI, ML, econometrics, software development, or other related technical skills and professional experience
Master's degree in Statistics, Financial Mathematics, Mathematics, Electrical Engineering, Physics, Econometrics, or Computer Science (preferred)
More than 1 year of hands-on experience with data science, ML/AI, or econometric modeling in industry or applied research settings (preferred)
Experience with programming languages and environments such as Python, R, Databricks, and React
Experience with LangChain, LangGraph, LangSmith, or other agentic frameworks (preferred)
Experience building and deploying machine learning models including XGBoost, random forests, and support vector machines (preferred)
Hands-on experience implementing DevOps practices for data, machine learning or AI systems, including automated testing, Continuous Integration / Continuous Delivery / Deployment pipelines, and infrastructure as code (preferred)
Track record of supporting business development efforts, including technical sales cycles and the client proposal process (preferred)
Demonstrated experience applying regulatory and risk management standards such as SR 11-7, Colorado SB21-169, NIST, ISO 42001, and the NAIC Model Bulletin (preferred)
Proven verbal and written communication skills, with the ability to translate complex technical concepts for non-technical audiences and engage with key stakeholders

Risk Modeling Services – Experienced Associate

Key skills