Proven track record of leading and collaborating on advanced analytics strategic initiatives; Proven track record of operationalization of analytic models in collaboration with marketing/risk and IT teams
Worked with large, unfiltered data sets or data science research
Has Knowledge of both structured and unstructured data
Scripting or programming experience: familiarity in programming languages with relational databases (e.g. Python, Java, Ruby, Clojure, Matlab, Pig, SQL);
Statistical Analysis: advanced usage of off-the-shelf tools such as R, SAS, SPSS, Weka and other analytical tools or software
Big Data: Experience with Big data tools such as HDFS, Cassandra, Storm
Database knowledge: skilled in structured database
Familiar with most of the following disciplines:
Conceptual modeling: to be able to share and articulate modeling;
Predictive modeling: most of the big data problems are towards being able to predict future outcomes;
Hypothesis testing: being able to develop hypothesis and test them with careful experiments;
Natural Language Processing: the interactions between computer and humans;
Machine learning: using computers to improve as well as develop algorithms;
Statistical analysis: to understand and work around possible limitations in models.
Degree in quantitative discipline such as Statistics, mathematics, Operations Research, Engineering, Computer Science, Econometrics or Information Science such as Business Analytics or Informatics
