Job Specifications
Description
Join a team where innovation meets impact. As aSenior Data Scientist, you will help drive the bank's adoption of Generative AI by leveraging Large Language Models (LLMs) to solve business problems, enhance customer experiences, and streamline internal operations. This role is ideal for someone with strong coding skills and experience in Natural Language Processing (NLP), who is excited to explore and apply emerging AI technologies in a practical, responsible, and scalable way.
Key Responsibilities
Apply LLMs and other Generative AI tools to solve real-world problems across the bank, including summarization, classification, information extraction, and conversational AI.
Source, clean, and prepare structured and unstructured data for model input and evaluation.
Conduct exploratory data analysis and apply statistical techniques to support model evaluation and refinement.
Collaborate with cross-functional teams including risk, compliance, and model validation to ensure responsible AI usage.
Stay current with advancements in Generative AI and NLP, and assess their applicability to banking use cases.
Document methodologies, findings, and model usage clearly for both technical and non-technical audiences.
Qualifications
Required:
4+ years of experience in data science, analytics, or applied machine learning.
Strong proficiency in Python and experience working in notebook environments.
Experience with NLP techniques and libraries (e.g., spaCy, NLTK, Hugging Face).
Demonstrated ability to work with unstructured text data and apply text processing techniques.
Experience sourcing and preparing data from various systems and formats.
Strong communication and collaboration skills, including technical writing and stakeholder engagement.
Preferred:
Exposure to Generative AI tools and pre-trained LLMs (e.g., GPT, Claude, Gemini).
Experience with creating robust orchestration plans to solve business problems.
Exposure to creating agentic workflows and systems.
Experience working with model validation teams or regulators.
Familiarity with prompt engineering and evaluation of LLM outputs.
Education
Required:Master's Degree in Computer Science, Mathematics, Statistics, or a related field.
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 onsite at a Citizens Corporate Office, 1 day remote
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Equal Employment Opportunity
Citizens, its parent, subsidiaries, and related companies (Citizens) provide equal employment and advancement opportunities to all colleagues and applicants for employment without regard to age, ancestry, color, citizenship, physical or mental disability, perceived disability or history or record of a disability, ethnicity, gender, gender identity or expression, genetic information, genetic characteristic, marital or domestic partner status, victim of domestic violence, family status/parenthood, medical condition, military or veteran status, national origin, pregnancy/childbirth/lactation, colleague's or a dependent's reproductive health decision making, race, religion, sex, sexual orientation, or any other category protected by federal, state and/or local laws. At Citizens, we are committed to fostering an inclusive culture that enables all colleagues to bring their best selves to work every day and everyone is expected to be treated with respect and professionalism. Employment decisions are based solely on merit, qualifications, performance and capability.
Why Work for Us
At Citizens, you'll find a customer-centric culture built around helping our customers and giving back to our local communities. When you join our team, you are part of a supportive and collaborative workforce, with access to training and tools to accelerate your potential and maximize your career growth
Background Check
Any offer of employment is conditioned upon the candidate successfully passing a background check, which may include initial credit, motor vehicle record, public record, prior employment verification, and criminal background checks. Results of the background check are individually reviewed based upon legal requirements imposed by our regulators and with consideration of the nature and gravity of the background history and the job offered. Any offer of employment will include further information.
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