Sorry, this job is no longer available.

Data Engineer - Center of Data Science Team


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 Data Engineer in its Center for Data Science and Analytics.

 

The Center for Data Science and Analytics is 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 are aided by New York Life’s existing business with a large market share in individual life insurance. We have the freedom to explore external data sources and new statistical techniques, and are excited about delivering a whole new generation of Analytical solutions.

 

In fact, we are designing and will build one of the first multivariate model-based continuous risk differentiations in the industry. This model will incorporate current underwriting best practices (including medical rules) as features and add other data sources, patterns/ideas and variables to essentially create a rating plan to support the next generation underwriting process at New York Life. This is just one of several projects with large business value. Geographic analytics on agents and customers, application fraud detection, agent success prediction and client prospecting analytics (off-line and on-line) are other exciting examples of enormous incremental value from analytics. Our products will be implemented into real-time core business processes and decisions that drive the company (e.g. underwriting, pricing, agent recruiting, prospecting, new product development).

We work with data ranging from demographics, credit and geo data to detailed medical data (medical test results, diagnosis, prescriptions) and social media information. We have a modern computing environment with a solid suite of data science/modeling tools and packages, and a large (but manageable) group of well-trained 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.

You will be part of Data & Platform sub-function team under Center for Data Science and Analytics. The Data & Platform team services internally to Data Scientists who focus on Statistical analysis.

You will be part of a fast paced, high-impact team who will work with an entrepreneurial mindset using some of the best of breed tools as part of our Enterprise Data Hub (Hadoop) using R, Spark and Python.

You will apply your data engineering skills to build pipelines, workflows to gather, cleanse, test and curate datasets from Oracle, MSSQL Server, 3rd party data and create datasets in Enterprise Data Lake (Hadoop), which will be used by several teams of predictive modelers.

You will perform Proof of Concepts and test out new software tools under the umbrella of Data Science but geared more towards data engineering.

Responsibilities

  • Ingests, merges, prepares, tests, documents curated datasets from various novel external and internal datasets for a variety of advanced analytics involving multi-variate models
  • Utilizes data wrangling/data matching/ETL techniques while to explore a variety of data sources, gain data expertise, perform summary analyses and curate datasets
  • Functions as data expert, contributes to analytics/solutions design and productizing decisions
  • Collaborate with Business leaders to understand business challenges and devise solutions by using business acumen and mining vast amounts of data to draw insights
  • Can work independently with some supervision and be part of a collaborative team
  • Work with Project Managers and Scrum Masters to provide milestones and stories
  • Proactively and effectively communicates in various verbal and written formats with senior level member of the team and partner
  • Actively participates in proof of concept tests of new data, software and technologies. Shares knowledge within the team
  • Follows industry trends and related data/analytics processes and businesses. Attends conferences, events, and vendor meetings as needed

 

Required qualifications

  • Graduate-level degree in computer science, engineering, or relevant experience in the field of Business Intelligence, Data Mining, Database Engineering, Programming
  • 3-5 years of overall experience working in the field of data wrangling and programming with a minimum of 1 year experience with ingesting, cleaning, merging and applying necessary data wrangling logic in Hadoop
  • 1+ years in writing complex SQL queries in any of the following and/or similar databases - Oracle, SQL Server, DB2, MySQL
  • Proficiency using Python for all data related work such as Numpy, Pandas, PySpark
  • Experience working with Linux Operating System
  • Experience working with data visualization tools or packages
  • Experience building Exploratory Data Analysis reports such as Histograms, Box plots, Pareto, Scatter Plot using R, Python or a Data Visualization tool such as Tableau and Spotfire

 

Preferred: 

  • Understanding of statistical modeling concepts, designs and analytics-based products
  • Any experience in using ETL tools such as Ab Initio, Talend, Informatica, Pentaho
  • Any experience working with Data Warehouses and/or Data Marts
  • Any experience in Life Insurance business

 

 

Other Notes:

Our technology stack is RStudio Pro, SAS, Enterprise Data Hub (using Hortonworks Hadoop Data Platform), Waterline, Trifacta, R, Python, Spark, PySpark, SparkR, Linux

 

 

EOE M/F/D/V

 

SF: LI-TK1

EF: EF-TK1

EOE M/F/D/V

 

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.