Required :
1. Strong quants. Basic math functions, basic statistics, normal distribution and linear regression.
2. Coding knowledge in R and Python. Numpy, Scipy, and Pandas.
3. SQL queries.
4. Data transforms - wide to long, transpose and pivot table, frequency, etc.
5. Familiarity with UNIX operating systems. RHEL/Ubuntu.
Good to have :
1. Experience with large datasets and some DB knowledge.
2. Experience in financial and survival data, customer lifecycle - acquisition, engagement, and attrition.
3. Logistic regression for propensity and default. ML models.
4. Meta and OO programming.
5. AWS knowledge - Glue, EC2, and Athena
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