Data Scientist

• Job Title: Data Scientist
• Location: Richmond, Virginia, United States
• Type: Full Time

Our Client is Looking a highly analytical and technically skilled Data Scientist – Model Risk Management & Generative AI Validation to assess, challenge, and validate advanced machine learning and AI models across enterprise business domains. This role combines data science, model risk management, and emerging AI technologies to ensure models are robust, reliable, and aligned with governance standards.

• Key Responsibilities
• Model Validation & Risk Assessment
• Validate machine learning, statistical, and AI models across multiple business functions
• Identify, assess, and quantify model risks through rigorous testing and analysis
• Develop challenger models to evaluate and benchmark production (“champion”) models
• Contribute to model governance frameworks and validation standards for next-generation AI solutions
• Machine Learning & Generative AI
• Build, test, and evaluate machine learning models using modern AI frameworks and tools
• Leverage technologies such as:
• PyTorch
• Hugging Face
• LangChain
• Vector Databases
• LLMOps platforms
• Support validation and risk assessment of Generative AI and Large Language Model (LLM) applications
• Data Analysis & Insights
• Analyze large-scale structured, unstructured, and multi-modal datasets
• Extract actionable insights to improve model performance and risk management processes
• Conduct statistical analysis, back-testing, and performance monitoring of predictive models
• Model Governance & Compliance
• Support development and enhancement of model governance frameworks
• Ensure validation processes align with internal policies and risk management standards
• Document findings, recommendations, and validation results comprehensively
• Stakeholder Collaboration
• Partner with data scientists, engineers, product managers, and business stakeholders
• Communicate complex model risks and technical findings to senior leadership and non-technical audiences
• Provide recommendations that influence model strategy and business decision-making

• What We're Looking For
• Technical Expertise
• Strong experience in:
• Machine Learning
• Statistical Modeling
• Predictive Analytics
• Model Validation
• Generative AI and LLM technologies
• Experience with:
• Python, Scala, or R
• Open-source ML frameworks
• Cloud platforms (AWS preferred)
• Knowledge of model evaluation techniques, including:
• ROC Curves
• Confusion Matrices
• Classification & Clustering Models
• Sentiment Analysis
• Time Series Modeling
• Deep Learning
• Data Science & Analytics
• Ability to work with large and complex datasets from diverse sources
• Strong quantitative, analytical, and problem-solving skills
• Experience designing experiments and validating model performance
• Innovation & Research
• Passion for staying current with emerging AI, machine learning, and data science technologies
• Ability to apply innovative approaches to complex business problems
• Interest in advancing Responsible AI and Model Risk practices
• Communication & Collaboration
• Strong presentation and stakeholder management skills
• Ability to explain technical concepts and model risks in business-friendly terms
• Experience working in cross-functional and collaborative environments

Qualifications

• Required
• Bachelor's degree in a quantitative field with 2+ years of data analytics experience, or
• Master's degree in a quantitative field (Statistics, Mathematics, Analytics, Computer Science, Economics, or related discipline)
• Experience applying machine learning and data science techniques to business challenges

Preferred

• Master's or PhD in a STEM field
• Experience with AWS cloud technologies
• 2+ years of experience in Python, Scala, or R
• 2+ years of hands-on machine learning experience
• Exposure to Generative AI, LLMs, and model governance frameworks