Senior AI Engineer

VantageScore•Washington, DC

7h•Hybrid

About The Position

We are seeking a highly motivated and innovative Senior AI Engineer to join our brilliant team of analytics professionals and developers, supporting the cutting-edge development of credit scoring models, generation of unique insights, and delivery of transformative technologies rooted in innovative value propositions. In this role, you will be essential to credit score model innovation, credit and open banking related research initiatives, pilot program analyses with lenders and fintech partners, and ongoing model monitoring and reporting processes. You’ll bring your expertise in GenAI/Large Language Models (LLMs) to advance our use of structured and unstructured data to deliver new products and insights. You’ll partner cross-functionally to deliver scalable AI-powered products and solutions that redefine how consumers engage with credit, also ensuring our models are accurate, explainable, and aligned with our mission to empower responsible lending and financial inclusion. Given team growth, we may hire more than one individual into this role.

Requirements

Master's or PhD in a quantitative field such as Data Science, Statistics, Computer Science, Engineering, or Econometrics
5+ years of experience in data science, machine learning, or AI/ML in a research or production environment
Strong programming skills in Python and experience with common data science and ML libraries
Proven experience building and deploying machine learning models (e.g., classification, regression, clustering, neural networks)
Hands-on experience working with large, complex datasets (structured and unstructured)
Experience with GenAI, NLP, and/or Large Language Models (LLMs), including fine-tuning and evaluation
Solid understanding of model validation, performance monitoring, and explainability techniques
Experience translating analytical results into clear, actionable insights for both technical and non-technical stakeholders
Strong problem-solving skills with the ability to navigate ambiguity and deliver business impact

Nice To Haves

Experience in credit risk modeling, financial services, or fintech
Understanding of fairness, bias mitigation, and responsible AI practices in high-stakes decision systems
Hands-on experience with explainability techniques (e.g., SHAP, LIME, feature attribution, surrogate models)
Experience deploying and maintaining ML models in production environments, including monitoring, retraining, and performance tracking
Track record of publishing research, white papers, or contributing to thought leadership

Responsibilities

Conduct advanced research on structured and unstructured data, developing insights to support product management and new product development.
Contribute to the design, development, evaluation, and deployment of machine learning (ML) models, including credit risk and predictive models.
Serve as the team’s expert on GenAI/LLMs, adapting and fine-tuning models and ensuring explainability and compliance.
Drive pilot program analyses, including back-testing, rejection inference, and performance analyses using diverse data sets.
Improve and maintain existing model monitoring processes and develop compelling data visualizations and dashboards to communicate key insights to stakeholders.
Partner with engineers to operationalize models into production systems, ensuring scalability and resilience at high data and inference volumes.
Research and apply emerging AI/ML, GenAI/LLM technologies, staying abreast of state-of-the-art methods, tools, and best practices.
Translate complex analyses into clear, actionable business recommendations for both technical and non-technical audiences.
Contribute to thought leadership through white papers, presentations, and insights shared internally and externally.