Senior Data Scientist - Customer Analytics
New York Life Insurance Company ("New York Life" or "the company") is the largest mutual life insurance company in the United States. Founded in 1845, New York Life is headquartered in New York City, maintains offices in all fifty states, and owns Seguros Monterrey New York Life in Mexico.
New York Life is one of the most financially strong and highly capitalized insurers in the business. The company reported 2016 operating earnings of $1.954 billion. Total assets under management at year end 2016, with affiliates, totaled $538 billion. As of year-end 2016, New York Life's surplus was $23.336 billion. New York Life holds the highest possible financial strength ratings currently awarded to any life insurer from all four of the major ratings agencies: A.M. Best, A++; Fitch AAA; Moody's Aaa; Standard & Poor's AA+. (Source: Individual Third Party Ratings Report as of 8/17/16).
Financial strength, integrity and humanity-the values upon which New York Life was founded-have guided the company's decisions and actions for over 170 years.
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 Senior Data Scientist in its Center for Data Science and Analytics.
The company has over 170 years of history and while usable data does not quite go back this far, we have a wealth of internal information on consumers, policies and their performance, as well as applicants, prospects and our 10,000 agents. We also have a multitude of external data from a great variety of sources. Analytical challenges range from consumer analytics (segmentation, response, conversion, retention, up-sell), media mix, mortality risk to agent recruiting decisions, fraud detection and digital analytics.
TheCenter for Data Science and Analyticsis the innovative corporate analytics group within New York Life. We are a rapidly growing entrepreneurial department which aims to design, create and offer innovative data-driven solutions for many parts of the enterprise. We explore external data sources and new statistical, machine learning and AI techniques and deliver a whole new generation of analytical solutions.
We work with big data ranging from demographics, credit and geo data to voice and text data, psychometric data and social media information. We have a modern computing environment with a suite of data science/modeling tools and packages, and a group of talented professionals at various levels to support you. Life insurance is on the verge of huge change. This is a chance to be part of, actually to drive, the transformation of an industry. Is this not why we became data scientists?
You willapply your machine learning expertise and problem-solving skills to work with internal stakeholders and external vendors to deliver complex analytics projects within our Service group.
You willapply your data and coding skills to ingest, wrangle and explore external and internal data to gain business insights, prepare data for modeling, build and validate predictive models, and support production deployment of models.
You willapply your Artificial Intelligence skills to work on projects such as text and speech analytics, sentiment analysis, chat bot development and enhancement.
- Contributes to data analysis and modeling projects in Service. This includes business requirements gathering, data reception and processing, data analyses and modeling, reports/presentations, results review with stakeholders, and implementation support
- Provides technical support, which includes strategic consulting, needs assessments, project scoping and the preparation/presentation of analytical proposals
- Utilizes data wrangling tools and advanced statistical/machine learning techniques to create high-performing predictive models and actionable insights to address business objectives and client needs
- Communicates effectively with internal stakeholders on product design, data specification, model implementations, with partners on collaboration ideas and specifics, with clients and account teams on project/test results, opportunities, questions
- Creates project plans to ensure projects are completed on time and within budget. Provides high quality ongoing customer support, answering questions, resolving issues and building solutions
- Assures compliance with regulatory and privacy requirements during design and implementation of modeling and analysis projects
- Actively participates in proof of concept tests of new data, software and technologies. Shares knowledge within Analytics group
- Follows industry trends and related data/analytics processes and businesses. Attends conferences, events, and vendor meetings as needed
- Master's or PhD degree in quantitative studies such as data science, statistics, math, economics, operations research, computer science, engineering
- 3+ years of experience with statistical modeling using large and complex datasets in business setting
- Strong verbal and written communications skills, listening and teamwork skills, and effective presentation skills
- Strong expertise in Natural Language Processing (NLP) and demonstrated experience in sentiment analysis, advanced text analytics skills such as applying word embeddings in predictive modeling
- Strong expertise in machine learning techniques such as neural networks/deep learning (TensorFlow/Keras), tree models (Random Forests and GBM/xgboost), linear/logistic regression, cluster analysis
- Strong expertise in statistical sampling, regularization techniques (Ridge, Lasso, elastic nets), variable selection techniques, feature creation and transformation, and model validation (hold-outs, CV, bootstrap)
- Strong expertise in data pull and manipulation in database systems (Oracle, Hadoop, etc.). Solid understanding of data model and data governance
- Substantial programming experience with almost all the followings: Python, R, H2O, SPARK, SQL, SAS (STAT, macros, EM), Hive/Hadoop. Familiarity with Git/GitLab
- Proficiency in creating effective and visually appealing PowerPoint presentations
- Experience in survival analysis, GLM, principal components is a plus
- Experience with data visualization (e.g. R Shiny, Tableau) is a plus
- Experience with insurance industry is a plus
If you have difficulty using or interacting with any portions of this Web site due to incompatibility with an Assistive Technology, if you need the information in an alternative format, or if you have suggestions on how we can make this site more accessible, please contact us at: (212) 576-5811.
Based on revenue as reported by "Fortune 500, ranked within Industries, Insurance: Life, Health (Mutual)," Fortune Magazine, June 17, 2016. See http://fortune.com/fortune500/ for methodology.
Total surplus, which includes the Asset Valuation Reserve, is one of the key indicators of the company's long-term financial strength and stability and is presented on a consolidated basis of the company.
1. Operating earnings is the key measure use by management to track Company's profitability from ongoing operations and underlying profitability of the business. This indicator is based on generally accepted accounting principles in the US (GAAP), with certain adjustments Company believes to be appropriate as a measurement approach (non GAAP), primarily the removal of gains or losses on investments and related adjustments.
2. Assets under management represent Consolidated Domestic and International insurance Company Statutory assets (cash and invested assets and separate account assets) and third party assets principally managed by New York Life Investment management Holdings LLC, a wholly owned subsidiary of New York Life Insurance Company.
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