Data Scientist (phd)

  • Bangalore
  • Confidential
  • 3-8 years
  • 30 Jul 2015

  • IT/ Information Technology, Business Analytics

  • Banking - Retail, Financial Services/ Capital Markets, KPO/ Analytics
Job Description

Role Description:

This role involves working with senior stakeholders in understanding and identifying the business requirements and needs. Developing and implementing advanced analytics approaches including statistical modelling, machine learning algorithms, text mining, web analytics etc. to answer business questions and drive actionable insights.
Individual in this role is expected to work with very large data sets (both structured and unstructured), data cleansing/transformation, feature engineering, apply statistical analysis, data visualization, data mining, design and develop algorithms and define path to implementation with IT teams.

Candidate Description

Candidate should be comfortable with various data types and structures: structured and unstructured data, static and streaming data, extensive prior experience in integrating data, profiling, validating and cleansing data
He/She should possess extensive knowledge of and experience in applying data mining and machine learning techniques in a professional context
High level of proficiency in statistical tools like SAS, R
Expertise in programming languages like Java/C/C++/Python
Experience with relational databases and SQL is a must
Relevant experience in Big Data platforms like Hadoop and its eco-system
Candidate will be expected to communicate analytical results in a way that is meaningful for business stakeholders and provides actionable insights.
Have the ability to discover new opportunities where advanced analytical techniques can be leveraged for solving business problems

Preferred Attributes

Relevant experience with an organization known for its cutting edge/ best-in-class applicability of advanced analytics and predictive modeling techniques
Masters Degree / PhD in a quantitative field (e.g., Computer Science, Economics, Engineering, Mathematics, Finance, Statistics, Operations Research)

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