Assistant Vice President

Position Summary

Principal Data Scientist

Generative AI (GenAI)

Key Responsibilities:

AI Strategy & Leadership

• Drive the strategic direction of Generative AI initiatives aligned with business objectives.
• Evaluate, prototype, and implement GenAI technologies (e.g., GPT, Claude, LLaMA, Stable Diffusion).
• Serve as an AI thought leader, influencing executive decision-making and shaping the company’s AI roadmap.
  

Model Development & Deployment

• Design and build advanced GenAI solutions, including prompt engineering, fine-tuning, and retrieval-augmented generation (RAG).
• Lead the end-to-end development and deployment of ML/GenAI models into production environments.
• Develop scalable architectures for serving LLMs and other foundation models.
  

Research & Innovation

• Stay at the forefront of GenAI advancements by engaging with academic research, open-source communities, and industry forums.
• Contribute to internal AI research initiatives and explore novel applications of generative models.
• Publish whitepapers, patents, or present at top AI conferences as applicable.
  

Cross-functional Collaboration

• Collaborate closely with data engineering, product, design, and business stakeholders to translate complex needs into AI-powered solutions.
• Educate teams on the capabilities, limitations, and ethical considerations of GenAI.
  

Mentorship & Governance

• Mentor and coach junior and mid-level data scientists.
• Establish best practices for model governance, ethical AI, bias mitigation, and model explainability.
• Define frameworks for AI evaluation, monitoring, and lifecycle management.
  

Required Qualifications:

• 15+ years of experience in data science, machine learning, or artificial intelligence.
• Demonstrated expertise in building and deploying GenAI solutions, particularly with large-scale language and vision models.
• Deep knowledge of ML/DL frameworks (e.g., PyTorch, TensorFlow, Hugging Face, LangChain).
• Strong programming skills in Python and experience with cloud-based ML platforms (AWS SageMaker, Azure ML, Vertex AI).
• Strong grounding in statistics, probability, optimization, and deep learning theory.
• Experience working with multimodal data (text, image, audio, video) and advanced NLP/NLG techniques.
  

Preferred Qualifications:

• Ph.D. or Master’s in Computer Science, Machine Learning, Mathematics, or related field.
• Experience with enterprise applications of GenAI (e.g., content generation, synthetic data, co-pilots, document understanding).
• Familiarity with MLOps and AI model lifecycle management in production environments.
• Knowledge of AI regulations, data privacy, and responsible AI frameworks.