Roles and Responsibilities:
- Proactively analyze data to answer key questions from stakeholders or out of self-initiated curiosity with an eye for what drives business performance, investigating and communicating areas for improvement in efficiency and productivity
- Hands-on experience on machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, time series, etc.
- Expert level knowledge & hands-on in using MS Excel for crunching large data and doing analysis.
- Working knowledge of SQL, PG SQL, VBA ,Python, R (preferred), Tableau and Spotfire (would be good to have).
- A familiarity with R and Python and an ability to understand intermediate data scraping techniques is required.
- Experience Acquiring data from primary or secondary data sources and preserving the data integrity of these sources.
- Good knowledge of fundamentals of statistics.
- Experienced In implementation of methodologies such as Annova, Z test, Fourier Analysis, box plots, normality test.
- Knowledge of basic DBA skills and understanding of data normalization & denormalization
Key Skills & Expertise (Specific requirement):
1. Knowledge of R Language
2. Python would be added advantage
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