Location Designation: Hybrid - 1 day per quarter
When you join New York Life, you’re joining a company that values career development, collaboration, innovation, and inclusiveness. We want employees to feel proud about being part of a company that is committed to doing the right thing. You’ll have the opportunity to grow your career while developing personally and professionally through various resources and programs. New York Life is a relationship-based company and appreciates how both virtual and in-person interactions support our culture.
New York Life, the largest writer of retail life insurance in the U.S. and a top player in annuities, long-term care, and mutual funds, is seeking a Lead Data Scientist in its AI and Data team.
The company has 179 years of history and while usable data does not quite go back that far, we have a wealth of internal information on consumers, policies, and their performance, as well as applicants, prospects and our 12,000 agents. We also have a multitude of external data from a vast variety of sources. Analytical challenges range from mortality risk to agent recruiting decisions, service optimization, consumer analytics (segmentation, response, conversion, retention, up-sell), fraud detection, advertising allocation and office footprint optimization.
When you join New York Life, you are joining a company that values career development, collaboration, innovation, and inclusiveness. We want employees to feel proud about being part of a company that is committed to doing the right thing. You will have the opportunity to grow your career while developing personally and professionally through various resources and programs. New York Life is a relationship-based company and appreciates how both virtual and in-person interactions support our culture.
New York Life’s AI and Data team delivers innovative data, insights, and AI solutions for the organization. Our AI team works on a diverse portfolio of AI and GenAI projects, by combining agile and entrepreneurial drive with industry-leading methods and tools. Our efforts are fully supported by executive leadership, and we work hand in hand with our Business Partners through all stages of model development from ideation to deployment. As it takes multiple skill sets to deliver AI models to production, our AI team includes product managers, data scientists, MLOps engineers, program managers, a model validation & governance group, and a communications & development group.
The Artificial Intelligence and Data (AI & D) Team is the innovative corporate data and analytics group within New York Life. We are a rapidly growing entrepreneurial department charged with the design and creation of innovative data-driven solutions for many parts of the enterprise. We have the freedom to explore external data sources and new techniques and are delivering exciting next generation solutions.
The Lead Data Scientist reports to AI lead of Field Productivity and Field Operations Value Streams. A good understanding of predictive analytics (including the process of building and deploying models) and technology is essential. Examples of Field and Agency sales Data Science products that have built and are currently working on are below.
Candidate Assessment Tool
Agent sales and retention forecasting models
Gen AI tools for Agents
Responsibilities
• Independently leads and contributes to data analysis and modeling projects from project/sample design, business review meetings with internal and external clients deriving requirements/deliverables, reception, and processing of data, performing analyses and modeling to final reports/presentations, communication of results and implementation support.
• Demonstrates to internal and external stakeholders how analytics can be implemented to maximize business benefits. Provides technical support, which includes strategic consulting, needs assessments, project scoping and the preparation/presentation of analytical proposals.
• Utilizes advanced statistical and machine learning techniques to create high-performing predictive models and creative analyses to address business objectives and client needs. Tests new statistical and machine learning analysis methods, software, and data sources for continual improvement of quantitative solutions.
• Implements analytical models into production by collaborating with technology and operation teams. Utilizes proper data visualization tools for model testing, modeling results and data patterns exhibition. Design performance metrics for model selection and performance monitoring.
• Utilizes data wrangling/data matching/ETL techniques while programming in several languages to explore a variety of data sources, gain data expertise, perform summary analyses and prepare modeling datasets. Deploys analytical solution in production systems.
• Proactively and effectively communicates in various verbal and written formats with internal stakeholders on product design, data specific
Location: New York, NY
Posted: Aug. 23, 2024, 7:49 a.m.
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