At MetLife, we seek to make a meaningful impact in the lives of our customers and our communities. Job Location
United States : New York : New York Alternate Job Location
Not Applicable : Not Applicable Job Description
The Marketing Data Scientist is in the Science of Marketing group, a new area within the Global Brand & Marketing department responsible for defining global standards and conducting global qualitative and quantitative research for customer insights, customer segmentation, marketing measurement and tracking.
This area and role will perform work related to:
- The design, development and execution of big data and analytics solutions aligned against operational and strategic data problems with a focus on marketing, communications and consumer experience design.
- The building of internal capabilities in the areas of insights, research and analysis to better serve our businesses, regions and countries.
- Research, data mining, predictive modeling and business analytics projects.
- Conduct research using leading edge statistical, data mining and predictive analytics tools.
- Builds or manages complex level statistical and data mining models.
- Assist in the assessment of key data sources.
- Partner with cross-functional partners to understand their business hypotheses; scope data science work appropriately based on this analysis to drive their objectives.
- Project work that deliver both tactical and strategic marketing insights to drive business results.
- Translate complex data into easily understood concepts for business utilization.
- Collect, analyze data for its use to and drive actionable and clear recommendations to the Business.
- Leverage data science tools and techniques to analyze large data sets to develop and customize models/algorithms used uncover trends, patterns and insights in the data.
- Assist in the integration of traditional insights for the development of more holistic and complete recommendations.
- Participate in the development of processes and approaches to improve the effectiveness and visibility of data science and the advancement of marketing analytics.
Marketing Analytics Skills (considerations):
- Partner with IT and other 'analytics' areas to develop best in class processes and techniques to leverage data science across MetLife.
- Builds strong working relations and improves workflow and organizational issues.
- Conceptual modeling: ability to share and articulate modeling.
- Statistical analysis: ability to understand and work around possible limitations in models.
- Predictive modeling: ability to utilize predictive analysis for future outcomes to address business problems.
- Hypothesis testing: being able to develop hypothesis and test them with careful experiments.
- Data visualization: creative in displaying information visually and making the patterns they find clear and compelling to business partners.
- 3+ years of experience developing algorithms and predictive models to address and solve business problems.
- 3+ years of experience in business/data setting with experience in data analysis, data stewardship, data modeling.
- Strong working knowledge of advanced data mining tools.
- Working knowledge of advance marketing analytic models such as MROI, customer lifetime value, segmentation, campaign measurement and testing, as well as basic web analytics.
- Working knowledge of marketing analytic tools such as SAS, R, Qlickview/Tableau/Domo, Business Objects.
- Focuses on Customers, produces results.
BA degree in Computer Science, Marketing Engineering, Statistics, Economics, Math, Finance, Science as well as any other related field of expertise. Business Category
Global Brand & Marketing Number of Openings
MetLife is a proud equal opportunity/affirmative action employer committed to attracting, retaining, and maximizing the performance of a diverse and inclusive workforce. It is MetLife's policy to ensure equal employment opportunity without discrimination or harassment based on race, color, religion, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity or expression, age, disability, national origin, marital or domestic/civil partnership status, genetic information, citizenship status, uniformed service member or veteran status, or any other characteristic protected by law.
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