Job Description :
Designs, develops, and implements algorithmic solutions for time series, streaming data, and big data at rest
Works with functional consulting teams across business domains, including Communications, Media, Entertainment, Oil & Gas, Manufacturing, Retailing, and Financial Services
Develops reusable, maintainable and effective predictive and behavioral models through rapid, iterative, Agile development using machine learning techniques.
Contributes to 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 analysis 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
Advanced 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.
5 to 10 years of experience as a data scientist or similar role in a consultancy, industrial or government scientific or engineering laboratory, manufacturing company, industrial engineering company, or financial services firm.
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, applied mathematics, regression, classification, anomaly detection, machine learning, neural networks, natural language processing and other analytical techniques.
Demonstrated in-depth knowledge or relational databases, object-oriented programming, and a statistical-programming environment.
Fluency with analytical software including R, Python, Stata, MatLab, SAS, and/or SPSS
Working knowledge of ETL tools such as Pentaho, Informatica, Lavastorm, Alteryx, or Talend
Working knowledge of Big Data environments and frameworks including HDFS, Spark, Impala, Hive, HBase, Cloudera, Azure, and GCP.
Data Visualization skills including tools such as Tableau and PowerBI
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
             

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