Analytics Manager - Decision Science Opportunity in Analytics

  • Bangalore
  • Confidential
  • 4-9 years
  • 07 Apr 2015

  • Business Analytics

  • KPO/ Analytics
Job Description

Roles & Responsibilities:

The candidate should have superior problem solving skills. The ability to understand a business problem & translate into statistical one is a must.
He/she should be able to decide on the best modeling/analysis techniques and provide actionable insights/ model algorithms to the business.


Model development & Deep-dive Strategic Analysis:

Data extraction: Extract data from appropriate sources in a complex warehousing environment. Require in-depth knowledge of data elements.
Data processing: Perform complex data processing (e.g. merging, sorting, data transformations) using SAS, Access, or other ETL tools on PC or Linux
Profiling and analysis: Combine in-depth business knowledge, insights, and techniques such as data visualization, cross-tabs, statistical tests, and data mining techniques to identify customer or prospect needs, behavioral trends, product preferences, and up-selling, cross-selling, and retention opportunities
Model development: Apply standard and cutting-edge techniques (statistical modeling, data mining, predictive analytics, machine learning, optimization) to identify drivers of a business metric (e.g. campaign response, attrition, propensity to buy, multi-channel marketing). Compare techniques using validation to arrive at the best model
Model scoring and business applications of modeling/analytics:
Insert developed models into the scoring process
Work with tech groups to ensure quality
Act as a consultant to the larger team and marketing sponsors on usage of models
Provide analytical inputs to campaign design for direct mail, email and live channels
Communication, Coordination & Presentation:
Work with a consultative mindset to gather requirements from marketing sponsors and other team professionals to identify the right requirements
Identify appropriate problem-solving approaches and get buy in from sponsors
Work with tech groups to identify and resolve any data, infrastructure, or implementation issues
Coordinate with other team professionals on model applications
Communicate modeling and analysis results and provide professional presentations to marketing sponsors in a simple yet actionable manner
Manage contractors, when appropriate


Data mining / predictive analytics / machine learning techniques
Advanced statistics
SAS (BASE, Unix, Stat, Eminer, Eguide, Model Manager)
SQL/PostGres SQL
Familiarity with Excel and Access
Knowledge of extracting and using data in warehousing environment
Knowledge of banking/financial services business
Marketing (including direct marketing) experience

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