Senior Associate - Data Scientist

 

Location Designation: Hybrid - 3 days per week 

 

 

Role Overview
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 will support the development of AI solutions, spanning traditional Machine Learning, Generative AI, and Agentic AI. The role focuses on building core technical skills, learning enterprise AI practices, and delivering well-defined components of AI solutions. You will collaborate closely with Data Scientists, Engineers, and product and technology partners while developing an understanding of model lifecycle management, responsible AI principles, and New York Life’s technology ecosystem.

What You’ll Do
· Execute AI/ML initiatives in partnership with data, technology, product and business teams.
· Deliver business-aligned OKRs, ensuring AI initiatives are outcome-driven and tied to enterprise value creation.
· 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 business tasks with human-in-the-loop checkpoints, escalation thresholds, and safety guardrails.
· Assit in implementing and refining 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 business 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, Machine Learning, AI, Engineering, Mathematics, Statistics, or a related quantitative field.
• 3-5 years of hands-on experience applying data, analytics, machine learning, or AI solutions to real-world business problems.
• Foundational knowledge of Machine Learning concepts, statistics, and data analysis techniques, with the ability to design and evaluate appropriate models.
• Proficiency in Python and SQL; working knowledge of core software engineering concepts (version control with Git/GitHub), testing and documentation.
• Working knowledge of Generative AI concepts (e.g., LLMs, prompt engineering).
• Exposure to Agentic AI architectures (e.g., tool-using agents, orchestration frameworks).
• Partner with business stakeholders to communicate model design and outcomes to both technical and non-technical audiences.
• Strong communication skills and a collaborative mindset.
• Proactive mindset and commitment to continuous learning.
• Experience in Life Insurance industry or consumer finance domains is a plus.

 

Pay Transparency

Salary Range: $100,000-$143,000 

Overtime eligible: Exempt 

Discretionary bonus eligible: Yes 

Sales bonus eligible: No 

Actual base salary will be determined based on several factors but not limited to individual’s experience, skills, qualifications, and job location. Additionally, employees are eligible for an annual discretionary bonus. In addition to base salary, employees may also be eligible to participate in an incentive program.