Key Responsibilities:

• Generative AI Research:
  Explore and evaluate Large Language Models (LLMs) and emerging generative AI techniques to identify impactful applications in data science.

• Model Fine-Tuning & Adaptation:
  Design and execute experiments to fine-tune or customize foundational models using domain-specific and internal datasets.

• Applied Generative AI Solutions:
  Leverage generative AI to enhance traditional machine learning use cases such as risk modeling, fraud detection, and customer analytics.

• Prompt Engineering & Evaluation:
  Develop effective prompting strategies and build robust evaluation and benchmarking frameworks to measure model performance and reliability.

• Cross-Functional Collaboration:
  Partner with data scientists and cross-functional teams to integrate generative AI capabilities into existing analytics and modeling workflows.

• Knowledge Sharing & Enablement:
  Act as a subject matter expert, driving adoption by sharing best practices, insights, and advancements in the generative AI space.

What We’re Looking For:

• 5+ years of hands-on experience
• Experience in data science, machine learning, or applied AI, with strong analytical and experimental skills.
• Experience with generative AI & large language models
• Hands-on experience working with large language models, building agents, prompt engineering, or model fine-tuning techniques.
• Strong proficiency in Python & Data Science Toolkit
• Extensive experience with Python-based data science tools and machine learning frameworks.