Job Responsibilities:

Lead the CCOR data science projects in designing, deploying, and managing advanced LLM and GenAI solutions for compliance and risk management.
Drive research and innovation in LLMs, GenAI, and related AI technologies to enhance model performance and address complex regulatory challenges.
Foster collaboration across cross-functional teams, including technology, compliance, and business stakeholders, to identify needs and deliver impactful solutions.
Oversee the development and maintenance of tools, frameworks, and processes for LLM model training, evaluation, and optimization.
Work with lead in analyzing and interpreting data to evaluate model effectiveness and identify opportunities for improvement.
Communicate complex technical concepts and project outcomes to senior leadership and non-technical stakeholders, enabling informed decision-making.
Work with team members, promoting a culture of innovation, continuous learning, and excellence.

Required Qualifications and Skills:

Master's degree or PhD in a quantitative discipline (e.g., Computer Science, Statistics, Economics, Mathematics) from a top-tier university.
2+ years of experience in AI/ML, with significant recent exposure to LLMs, GenAI, and NLP technologies.
Proven track record in developing and deploying AI solutions in compliance, risk, or related domains.
Advanced programming skills in Python, with deep experience in frameworks such as PyTorch, TensorFlow, and NLP libraries (e.g., Hugging Face Transformers).
Strong knowledge of LLM architectures, transformers, and language modeling.
Experience in data pre-processing, feature engineering, and advanced data analysis.
Exceptional problem-solving skills and the ability to communicate ideas and results clearly to diverse audiences.
Familiarity with regulatory requirements and risk management practices in financial services is highly desirable.

Associate - Data Science / Applied AI ML