Job Profile:
Fiserv is a market leader in building transaction systems for commercial banks in the US. Roughly $1.3T moves through the Fiserv system annually and 1.7B transactions are recorded on Fiserv systems also. Fiserv is roughly a $5B annual revenue company and has 20,000 employees globally. Fiserv also has 16,000 banking customers. Fiserv has invested heavily in generating insights into its customer behavior using analytics for internal and external customers. The marketing team is embarking on an ambitious phase-2 project of its customer experience system (CES) to analyze B2B customer behavior and generate insights to executive management to drive decision making. We are building an analytics team based in India to support this initiative.

Designation: Sr. Statistician

Job location: Bangalore

Experience: 3+ years overall

Reports into: Sr. Manager Analytics

Role overview:
As a Statistician, you will be engaged in multiple projects around marketing campaign and survey analytics. You will be generating actionable insights using descriptive and predictive analytical techniques for this project.

Key responsibility areas:
° Conduct analysis to identify key drivers of customer loyalty, brand perception based on analysis of survey data
° Developing perceptual maps to establish relationships between multiple customer attributes using techniques like correspondence analysis etc.
° Customer segmentation using techniques like CHAID, Cluster analysis
° Generate actionable insights into customer behavior by analyzing marketing data over period of time and correlating multiple customer attributes (applying various hypothesis testing techniques)
° Strong data preparation capabilities
° Strong SAS or SPSS skillset
° Handle multiple tasks with different priorities
° Work under minimal supervision and display strong independent behavior

Need to Have

° Masters in Statistics or Economics / Econometrics or equivalent experience.
° 2+ years of experience in analytics domain.
° Good exposure and hands on with various Modeling Techniques: Predictive Modeling - Logistic Regression Modeling, CHAID, CART, segmentation Modeling – Factor & Cluster analysis (Discrimination, Conjoint, perceptual mapping)
Good to Have
° Base/Advance SAS certification

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