Principal Data Scientist- Generative AI

As a Principal Data Scientist, you will lead the strategic application of Generative AI across the bank, leveraging Large Language Models (LLMs) to drive innovation, improve operational efficiency, and enhance customer and employee experiences. This role requires deep expertise in NLP, hands-on experience with Generative AI tools, and the ability to guide teams in responsibly integrating these technologies into business processes.

Key Responsibilities

• Lead the design and implementation of solutions using LLMs and Generative AI tools for complex workflows and processes.
• Partner with business, risk, compliance, and technology teams to identify high-impact use cases and ensure responsible AI deployment.
• Guide data preparation efforts, including sourcing, cleaning, and structuring data for LLM input and evaluation.
• Evaluate model performance, conduct error analysis, and iterate on prompt engineering and fine-tuning strategies where applicable.
• Stay ahead of emerging trends in Generative AI and NLP, and assess their relevance to banking applications.
• Mentor junior data scientists and contribute to the development of best practices for AI adoption across the organization.
• Communicate technical concepts and findings clearly to executive stakeholders, regulators, and cross-functional teams.

Qualifications

• Required:
  • 7+ years of experience in data science, machine learning, or applied AI.
  • Proven experience applying Generative AI and LLMs in production or pilot environments.
  • Strong proficiency in Python and experience with NLP libraries and frameworks (e.g., LangChain, Autogen, Strands, etc.).
  • Deep understanding of NLP techniques and their practical applications.
  • Experience working with unstructured data and integrating AI solutions into business workflows.
  • Strong communication and leadership skills, including technical writing and stakeholder engagement.
• Preferred:
  • Experience with prompt engineering, model evaluation, and LLM orchestration.
  • Familiarity with cloud platforms and MLOps tools.
  • Experience interacting with model validation teams and regulators.

Education

• Required: Master’s or Ph.D. in Computer Science, Mathematics, Statistics, or a related field.

Hours & Work Schedule

• Hours per Week: 40
• Work Schedule: Monday - Friday
• Hybrid: 4 days on site at a Citizens Corporate Office, 1 day remote

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