• Conduct quantitative analysis including hypothesis testing and root-cause analysis on large data sets with more autonomy • Support the working group by identifying types of information needed for analysis or to inform business questions create data structures/transformations to be leveraged by groups for analysis • Use statistical analysis and machine learning to develop, maintain, and anticipate considerations in implementation of models that address the right business need • Use critical thinking to use the right approach for each problem statement • Anticipate business need and make continuous improvements to models and processes

• Presales solution design & value articulation, explaining to clients the analytic details of FICO Scores products, features, analytics and services. • Partnership with Scores Sales Executives and Client Success Managers to understand client business objectives, use cases, decision criteria, and to ensure informed handoff from presales to post‑sale execution. • Design and articulate FICO Score solution configurations aligned to client needs, regulatory context, and operational realities. • Lead technical discovery sessions, solution walkthroughs, and value‑based discussions with client stakeholders. • Translate analytics, model performance, and score usage into clear business and ROI narratives for executive and technical audiences. • Support presales activities across new logo, expansion, and renewal motions, including solution positioning and packaging. • Contribute to pricing discussions by providing technical input, usage assumptions, and solution complexity considerations. • Partner cross functionally with Sales, Analytics and Clients Success, to support RFx responses, proposals, and deal review materials. • Review and validate client‑facing materials (presentations, ROI models, solution summaries) for accuracy and relevance.

• Lead Generative AI and LLM-driven projects • Design and optimize AI architectures for scalable production systems • Develop and deploy production-grade Python AI solutions • Implement Retrieval-Augmented Generation (RAG) pipelines • Mentor engineers and data scientists • Collaborate with engineering teams on cloud-native architectures • Ensure AI solutions are reliable, scalable, and maintainable

• Create advanced machine learning analytical solutions to extract insights from diverse structured and unstructured data sources • Unearth data value by selecting and applying the right machine learning, deep learning and processing techniques • Refine data manipulation and retrieval through the design of efficient data structures and storage solutions • Innovate with tools designed for data processing and information retrieval • Dissect and document vast datasets, analyzing them to highlight patterns and insights • Solve complex challenges by developing impactful algorithms • Ensure model excellence by validating performance scores and analyzing Return on investment and benefits