Statistician - SAS/SPSS/R/SQL - KPO

Statistician would be responsible for building predictive models and developing machine learning algorithms. Develop various analytics scorecard for bankers to run their business, to grow revenue, maximize efficiency and reduce risk in day to day level operations and banking Business

Main Focus and Challenges:

- Accountable for developing new cutting edge predictive models and machine learning algorithms like ANN, Random Forest, SVM regression, Gradient Boosting Model, K-means nearest neighbor, Discriminant Analysis, Logit & Probit regression model, Decision tree, etc and also responsible for analytics processes execution, transformation and governance.

- Develop optimization algorithm in addition to Predictive model to optimize the price & marketing spend to achieve maximum ROI.

- Support the analytics technology team of big data experts to understand the analytical solution developed for them to implement this in the analytical infrastructure whether its offline or real time decision systems

- Candidate should have good level of familiarity and proficiency in developing solutions like Customer life time value, Next best product propensity, Attrition predictive model, Survival predictive model, Need, value & behavioral segmentation, Driver of profitability, relationship optimizer, PAU for payment and banking channels, response model development, price elasticity model and optimization.

Qualifications & Experience:

- Master Degree in Statistics/Economics/Mathematics

- 2+ years of experience, with the last 1-2 years in building predictive models for retail banking business, debit card and credit card industries. Must have also managed analytics delivery on a day to day level work.

- Must have the ability to perform descriptive analytics and data mining of results from models to support the Business Analyst to generate insights from the analytical work.

- Strong programming skills in SAS, SPSS, R and SQL.