Explore large datasets to surface useful trends, signals, and segments. The role drives business and industry solutions focused on Big Data and Advanced Analytics, in diverse domains such as product development, pricing, marketing research, public policy, optimization and risk management.
The role uses analytics to provide predictive, prescriptive, and decisive insight:
Translate business objectives into analytic approaches, and identify data sources to support analysis.
Analyze and model structured data using advanced statistical methods
Perform exploratory data analyses, generate and test working hypotheses, prepare and analyze historical data and identify patterns.
Analyze data using SAS, R, Python, Java, open source packages and commercial/enterprise applications.
Perform machine learning, text analytics, and statistical analysis methods, such as classification, collaborative filtering, association rules, sentiment analysis, topic modeling, time-series analysis, regression, statistical inference, and validation methods.
Implement algorithms and software needed to perform analyses
Drive client engagements focused on Big Data and Advanced Business Analytics, in diverse domains such as product development, marketing research, public policy, optimization, and risk management.
Interface with databases (SQL, NO SQL, HDFS) to extract, transform and load data
Communicate results and educate others through reports and presentations.
Essential skills required
Education / professional qualifications
Masters, or PhD in Computer Science, Statistics, MathematicsPrior Experience:
Masters, or PhD in Computer Science, Statistics, Mathematics, Engineering, Bioinformatics, Physics, Operations Research, or related fields, with relevant experience
Ability to break down complex problems, and develop strategies to solve them
Masters, or PhD in Computer Science, Statistics, Mathematics, Engineering, Bioinformatics, Physics, Operations Research, or related fields, with 2 - 9 years of relevant experience
Strong mathematical background with ability to understand algorithms and methods from a mathematical viewpoint and an intuitive viewpoint.
Expertise in at least one of the following fields: machine learning, data visualization, statistical modeling, data mining, or information retrieval
Develop and apply machine learning, and statistical analysis methods, such as classification, collaborative filtering, association rules, time-series analysis, advanced regression methods and hypothesis testing
Strong data extraction and processing, using NoSQL, MapReduce, Pig, and / or Hive preferred
Experience with command-line scripting, data structures and algorithms
Ability to work in a Linux environment, and process large amounts of data in a cloud environment
Proficiency in analysis (e.g. R, SAS) packages, and programming languages (e.g. Java, Python, Ruby)
Behavioral / team skills
Personal drive and positive work ethic to deliver results within tight deadlines and in demanding situations
Flexibility to adapt to a variety of engagement types, working hours and work environments and locations, strong time management skills
Excellent written and verbal communication skills Team player; self-driven and ability to work independently
Team player; self-driven and ability to work independently