Senior Associate, Data Scientist

New York Life•Tampa, FL

4d•$80,000 - $110,000•Hybrid

About The Position

As a Senior Associate, Data Scientist on the Advanced Analytics team, you will lead and deliver data-driven insights and analytical solutions that support key business initiatives across New York Life Direct. Working as part of a collaborative team, you will apply statistical analysis, experimentation, and machine learning techniques to solve real-world business problems across marketing, underwriting, actuarial, operations, and fraud prevention. In this role, you will independently translate business questions into analytical frameworks, own the delivery of scalable analytics solutions, and contribute to the team’s overall impact.

Requirements

Strong academic foundation in a quantitative field such as Data Science, Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related discipline, along with professional experience applying data science or analytics to solve a broad range of business problems.
Working knowledge of programming languages such as Python or R and familiarity with SQL, along with a solid grounding in statistical analysis, machine learning concepts, and data manipulation.
Comfortable working with real-world datasets and can independently translate data into meaningful, actionable insights.
Communicate clearly and effectively with both technical and non-technical audiences and can influence stakeholders through data-driven recommendations.
Demonstrate sound judgment, attention to detail, and the ability to manage multiple priorities, along with a strong commitment to continuous learning.
Master’s degree in a quantitative field (or equivalent experience)
Typically, 1–3+ years of experience applying data science or analytics in a business or applied setting
Experience with Python and/or R, and familiarity with SQL
Strong foundation in statistics, machine learning, and analytical problem-solving
Demonstrated ability to independently execute end-to-end analytical projects
Experience working with real-world datasets and delivering actionable insights
Strong communication skills with the ability to influence both technical and non-technical stakeholders
Ability to work independently with minimal supervision and manage competing priorities

Nice To Haves

Exposure to experimentation, model evaluation, or model monitoring
Experience in financial services, insurance, or direct-to-consumer businesses
Familiarity with cloud-based tools and platforms (e.g., AWS, Sagemaker)
Experience applying generative AI in business settings

Responsibilities

Own data science projects and/or key analytical workstreams across the full lifecycle, including problem framing, data exploration, feature engineering, model development, evaluation, and communication of results.
Apply statistical and machine learning methods to analyze structured and unstructured data, generating insights that directly inform business decisions and strategies.
Proactively define business problems and translate them into analytical approaches, delivering clear, actionable recommendations.
Lead the development, testing, and deployment of models in partnership with engineering teams, applying best practices in model lifecycle management.
Identify opportunities to improve processes, enhance model performance, and drive efficiency.