October 14, 2021

  • Performs Data Exploration & Discovery using deep dive analysis and interprets the results to develop actionable insights.
  • Extraction, exploration, and manipulation of large and complex data sets.
  • Help internal stakeholders in understanding, interpreting and analyzing massive data sets
  • Come up with sensible analytical methodologies using a combination of descriptive and inferential statistical methods to perform exploratory data analysis.
  • Craft easy-to–consume narratives and actionable insights from complex concepts with advanced data visualization and presentation skills
  • Acts as analytics consultant to internal business users and serve as point person for questions related to data, measurement methodology and analytical techniques
  • Support internal stakeholders in using data and various analytical tools to generate and communicate insights
Junior Level:
  • At least 1 year experience in customer analytics domain covering most of the following: data mining, data analytics, insighting, statistical analysis, large scale data acquisition, transformation, and cleaning, both structured and unstructured data.
  • Degree in a quantitative discipline such as Statistics, Mathematics, Computer Science, Econometrics or Information Science such as Business Analytics or Informatics
  • Has knowledge of both structured and unstructured data
  • Must possess core competencies, understanding and relevant experience in:
o Scripting or programming experience: familiarity in programming languages with relational databases
o Data Analysis and Visualization tools: hands on experience with tools such as Tableau, Python, R, Spark and other analytical tools or software.
Mid-Level:
  • At least 2-3 years of experience in customer analytics domain covering most of the following: data mining, data analytics, insighting, statistical analysis, large scale data acquisition, transformation, and cleaning, both structured and unstructured data
  • Degree in a quantitative discipline such as Statistics, Mathematics, Computer Science, Econometrics or Information Science such as Business Analytics or Informatics
  • Familiar with most of the following disciplines:
o Descriptive Statistics: being able to define the appropriate summary statistic to use in data profiling
o Hypothesis Testing: being able to develop hypotheses and test them with careful experiments