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Description: The Data Mining Scientist (DMS) uses tools from machine learning and statistics to discover patterns and knowledge in large volumes of data. The DMS builds predictive, anomaly, and pattern detection models where appropriate to solve a complex business information problem. The DMS leverages a broad range of data mining technologies including neural networks, decision trees, clustering, association rules, and Bayesian methods. The DMS works directly with the business to map a business problem into a data mining opportunity and selects the appropriate technology for the given problem. The DMS helps identify the relevant data sources and performs various data preprocessing steps to prepare the data for data mining.

The DMS typically works on complex problems where the business has little or no expert knowledge. The DMS is highly skilled at documenting and presenting analytical results to a non-technical audience. The DMS anticipates and overcomes operational obstacles in completing the analytical solution. The DMS ensures that the solution minimizes assumptions and inconsistencies that create uncertainty about the conclusions. The DMS must be proficient at the following analytical techniques:

1. Ad-Hoc Database Queries/Analysis
2. Exploratory Data Analysis
3. Data Cleansing
4. Data Visualization
5. Basic statistical Measures including:
   • Mean/Median/Mode
   • Standard Deviations
   • Histograms
6. Data Mining Techniques
   • Predictive Modeling
   • Anomaly/Outlier Detection
   • Automated Pattern Detection
   • Link Analysis
7. Machine Learning Algorithms
   • Neural Networks
   • Support Vector Machines
   • Regression
   • Decision Tree Induction
   • Naive Bayes
   • Clustering methods
   • Association Rules
   • Genetic Algorithms

Tools Typically Used

• Excel
• SAS or statistical tools
• SQL Database (MySql, Oracle, Sybase)
• Clementine, WEKA or similar data mining tools
• Programming Languages (Java/C/PHP, etc)

Contact:
How to Apply: To apply for this position, Click Here.

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