Senior Associate - Senior Data Scientist

As part of the Artificial Intelligence & Data (AI&D) organization, you will contribute to New York Life’s digital transformation by developing and deploying AI and machine learning solutions that enhance efficiency and improve client, agent, and employee experiences. 

This role focuses on Service operations (contact centers, claims, field service), where you’ll apply both Generative AI and traditional ML techniques to automate tasks, generate insights, and support decision-making. You’ll work closely with senior data scientists, engineers, product and technology partners to deliver impactful production-ready solutions that are safe, reliable, and aligned with business priorities. 

What You’ll Do: 

• Execute AI/ML initiatives for Service operations in partnership with data, technology, product and business teams. 

• Contribute to the end-to-end model lifecycle: data exploration, feature development, model training/validation, deployment, monitoring, and iteration. 

• Develop and help operationalize models using AWS (e.g., SageMaker, Bedrock) and modern data platforms (Snowflake, Databricks), ensuring quality, security, and scalability; partner with ML engineers for large-scale production deployment and scaling. 

• Assist in designing and evaluating agentic/AI-powered solutions that automate routine service tasks with human-in-the-loop checkpoints, escalation thresholds, and safety guardrails. 

• Implement and refine LLM/RAG approaches (vector stores, embeddings, retrieval optimization, prompt orchestration) with evaluators for reliability. 

• Ensure AI capabilities are accessible through APIs, dashboards, and integrated workflow applications used by service teams. 

• Build lightweight UI prototypes (e.g., Streamlit) to validate usability and support adoption. 

• Adhere to model governance, documentation, testing, and CI/CD best practices in partnership with MLOps. 

What You’ll Bring:

• Advanced degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative field. 

• 5+ years of experience applying data science and AI/ML to real-world business problems. 

• Ability to communicate complex ideas simply, presenting impact, trade-offs, and recommendations to non-technical partners. 

• Proficiency in Python and SQL; working knowledge of core software engineering concepts (version control with Git/GitHub, testing, logging). 

• Experience with AWS services (e.g., SageMaker, Bedrock) and modern data ecosystems (Snowflake/Databricks). 

• Working knowledge of LLMs, RAG architecture, and agent frameworks, including safe automation design and evaluation practices. 

• Solid grounding in ML methods (supervised and unsupervised learning, gradient boosting exposure to deep learning), feature engineering, regularization, cross-validation. 

• Ability to translate analytical findings into clear business insights and collaborate effectively with cross-functional partners. 

• Experience in customer service or consumer finance domains is a plus. 

This role involves limited travel (<10%) to events and vendor meetings.