Job Description :
Data Scientist
Travel : Mon - Thursday (100% Travel)
Fulltime / Permanent Position

Role description:
Develops reusable, maintainable and effective predictive and behavioral models through rapid, iterative, Agile development using machine learning techniques.
Contributes to Hitachi Solutions through a full Agile Software Development Life Cycle methodology.
Works closely with industry Subject Matter Experts, Data Architects and Solution Architects to understand business problems, identify data sources, develop analyzers and predictive models and configure visualization software to communicate results.
Applies intellectual curiosity and deep analytical thinking to mine large data sets for hidden gems of insight and correlation.
Actively seeks new methodologies, algorithms, tools and technologies to improve existing models and build new state-of-the-art models.
Education and Experience
Bachelor’s degree in a quantitative field such as Mathematics, Physics, Physical Chemistry, Statistics, Actuarial Science, Engineering, Economics, or related field from a four-year college or university. Master’s degree or higher preferred.
5 to 10 years of experience in an industrial or government scientific or engineering laboratory, underwriting firm, risk-management firm, or sell-side financial house.
Fluency with analytical software including R, Python, Stata, MatLab, SAS, and/or SPSS
Extensive experience applying machine learning algorithms, predictive modeling, data mining, and statistical analysis to solve business problems.
Dexterity and nimbleness with the Microsoft Office/VBA stack
Desired Skills and Abilities
Demonstrated in-depth knowledge of statistics, relational databases, object-oriented programming, and a statistical-programming environment.
Working knowledge of ETL tools such as Pentaho, Informatica, or LavaStorm
Excellent verbal, written and presentation skills
Success at executive presentations as well as influencing using data
Successful experience in negotiation and influencing at all levels within the organization