Data Scientist (Artificial Intelligence)

Location

Job Scope

Credit Risk Modeling and Analysis (50%)

• Develop and refine alternative credit scoring models using machine learning techniques and non-traditional data sources.
• Analyze diverse datasets to uncover patterns and trends in credit risk, particularly for underserved populations.
• Collaborate with risk management teams to implement effective credit assessment strategies.
• Create clear data visualizations and reports to communicate insights to stakeholders.
• Enhance model performance through rigorous testing and validation.
• Address ad hoc data analysis requests, delivering timely and actionable insights.

AI Solution Development and Integration (50%)

• Design and develop AI applications to streamline operational workflows and boost business efficiency.
• Implement and optimize Large Language Models (LLM) and Optical Character Recognition (OCR) solutions.
• Optimize LLM models for improved performance and scalability.
• Partner with software engineering teams to seamlessly integrate AI solutions into existing platforms.
• Deliver rapid prototypes or proof-of-concepts to address time-sensitive AI challenges.

Requirements

• Bachelor’s or Master’s degree in Data Science, Artificial Intelligence, Computer Science, Statistics, or a related field.
• 1 to 4 years of experience in data science, with exposure to credit risk modeling and/or AI applications development.
• Advanced proficiency in Python and SQL.
• Expertise with machine learning frameworks (e.g. PyTorch, scikit-learn, or equivalent).
• Familiarity with cloud platforms (e.g. AWS) and containerization (e.g. Docker) is a plus.
• Knowledge of LangChain and LangGraph is highly desirable.
• Excellent communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
• Strong analytical and problem-solving abilities with meticulous attention to detail.
• Flexibility to manage multiple projects and meet tight deadlines in a fast-paced environment.