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Advanced Analytics - Senior Associate
New York Life Insurance
New York, NY, United States
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New York Life Insurance Company is the largest mutual life insurance company in the United States. Founded in 1845 and headquartered in New York City, New York Life reported 2017 operating earnings of $2.06 billion. Total assets under management at year end 2017, with affiliates, totaled $586 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 independent rating agency commentary as of 8/1/17).
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.
Do you enjoy problem solving and thrive in an environment where you have freedom and autonomy to develop solutions? Do you love exploring data, searching for “diamond in the rough” insights? Are you an innovative, outside-the-box thinker who is comfortable with each step of the analysis process, from framing the problem and collecting the data to performing the analysis and sharing your findings? Are you eager to be part of transformational initiatives that raise an organization’s profile as an analytic competitor?
If you answered yes to these questions, you might be a great fit for our team. This position reports to the Head of Advanced Analytics in New York Life’s Retail Annuities business. As a member of the Strategy, Research, and Analytics team, you have the unique opportunity to leverage your data mining and analytics skills to uncover business opportunities and help shape the strategic direction of the Retail Annuities business. We have a wealth of data available at our fingertips, and we are looking for your help to unlock its full potential.
Responsibilities
In this role you will:
• Solve complex questions that may require innovative framing, rigorous deep-dives and/or statistical analysis
• Utilize your data mining and segmentation skills to identify new strategic opportunities for the Retail Annuities business
• Partner with members of Marketing, Sales, Product, and Service to identify their analytical needs, and develop solutions to support them
• Promote a test & learn strategy by assisting other parts of the RA organization with experimental design, measuring results, and recommending improvements based on your findings
• Collaborate with other analysts and data scientists within the Retail Annuities analytics team as well as in other analytics departments to share best practices, leverage analytical techniques, and champion an organizational culture where data is central to decision making
Qualifications
• Passion for data, with a curious mindset and a knack for problem solving
• Highly autonomous, independent and innovative thinker
• 4+ years of experience in an analytical role, where data analysis is a significant part of job function
• Strong oral and written communication skills, including ability to summarize or present complex topics to non-technical audiences
• Experience executing multiple end-to-end analytics projects, with demonstrated ability in each of the following areas:
◦ Framing the analysis
◦ Sourcing data from the appropriate databases
◦ Analyzing data through segmentation, visualizations, and statistical analysis
◦ Acquiring insights and developing recommendations
◦ Communicating results via presentations and Powerpoint decks
• Proven experience preparing and utilizing with large datasets, including:
◦ Querying databases
◦ Merging files
◦ Aggregating records
◦ Data transformations
• Proficiency with at least one statistical software packages (e.g., R, Python, or SAS)
• Proficiency with data querying languages (e.g., SQL or Hive)
• Preferred - Experience with analytic techniques including:
◦ Statistical analysis (e.g., t-tests, confidence intervals)
◦ Regression analysis/basic supervised learning techniques
◦ Experimental design (control groups, sample size calculations)
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EOE M/F/D/V
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