Data Science Manager- Generative AI

DescriptionOverviewAs a Data Science Manager, you will lead a team focused on applying Generative AI and Natural Language Processing (NLP) to solve complex business challenges across the bank. This role emphasizes the use of pre-trained Large Language Models (LLMs) and other out-of-the-box Gen AI tools to deliver scalable, responsible, and innovative solutions. You’ll guide technical execution, mentor data scientists, and collaborate with stakeholders to ensure alignment between AI capabilities and business needs.Primary ResponsibilitiesLead the development and deployment of Gen AI-powered solutions using LLMs for complex workflows and processes.Manage and mentor a team of data scientists, providing technical guidance, career development support, and performance feedback.Partner with business and technical stakeholders to identify high-value opportunities for Generative AI and define solution strategies.Oversee data sourcing, preparation, and transformation efforts to support model input and evaluation.Ensure responsible AI practices by collaborating with risk, compliance, and model validation teams.Drive prompt engineering, model evaluation, and iterative refinement of LLM-based solutions.Stay current with advancements in Generative AI and NLP, and assess their applicability to banking use cases.Contribute to the development of internal standards and best practices for Gen AI adoption.QualificationsRequired : 6+ years of experience in data science, machine learning, or AI, with at least 2 years in a leadership or managerial role.Hands-on 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, Langgraph, Autogen, Strands etc.).Proven ability to lead technical teams and manage multiple projects simultaneously.Experience working with unstructured data and integrating AI solutions into business workflows.Strong communication skills, including technical writing and stakeholder engagement.Preferred : Experience with prompt engineering and LLM orchestration.Familiarity with cloud platforms and MLOps tools.Experience interacting with model validation teams and regulators.Background in Agile methodologies and project management tools.EducationRequired :  Master’s Degree or PhD in Computer Science, Mathematics, Statistics, or a related field.Hours & Work ScheduleHours per Week : 40Work Schedule : Monday - FridayHybrid : 4 days on site at a Citizens Corporate Office, 1 day remote#LI-Citizens1

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Equal Employment OpportunityCitizens, 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 UsAt 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.