Responsibilities

Perform processing, cleansing, and verifying the integrity of data used for analysis

Do ad-hoc analysis and present results in a clear manner

Extend the data with third party sources

Enhance data collection procedures to include relevant information for the analysis

Select features, build and optimize classifier models using machine learning techniques

• Proficient in SDLC (Planned Iterative, Agile)
• Good spoken and written English language skills
• Good understanding of machine learning techniques such as Decision Trees, Naïve Bayes, SVM, Neural Networks
• Good experience with Python (preferred) but also R or C/C++
• Experience with at least one of the data science toolkits, such as R, numpy, scikit-learn, Weka, Matlab.
• Experience in using query languages such as SQL
• Experience with at least one NoSQL database (such as MongoDB, Cassandra)
• Experience in using visualization tools
• Good applied statistics skills, such as distributions, statistical testing, regression

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