KPMG - Data Scientist

Role: Data Scientist

Role Overview: 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.

Role Summary Description:

- 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.

Functional/Technical Skills:

- 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 5+ 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)