- Data Scientist would be responsible for building analytical solution using machine learning algorithms and predictive models.
- Develop a decision making contrivance for bankers to run their business, to grow revenue, maximize efficiency and reduce risk in day to day level operations and banking business.
- Data scientist would be part of core analytics solution advisory team at XXXX
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.
Job Description :
- Predictive model to optimize the price & marketing spend to achieve maximum ROI.
- Work closely with core analytics group and help to design front line decision making solution application.
- 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 (like dashboards) or real time decision systems (like trigger generation systems)
Accountable for mentoring, guiding junior data science staff at XXXX .
- 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 (Penetration Activation and Utilization analysis) for payment and banking channels, response model development, price elasticity model and optimization.
- Candidate should have experience with one or may banking data sources such as Retail, Commercial, Cards, Payments and Acquiring Banking Business etc.
- Understanding of core transaction data, customer demographic & psychographics, CRM, third party and web data, etc. is a must.
Qualifications & Experience:
- Master Degree in Statistics/Economics/Mathematics /Quantitative Methods .
- 4+ years of experience, with the last 2-3 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.
- Data Scientist should have strong banking domain knowledge in CASA, personal loan, Saving, Mortgage, HELOC, IRA, debit and credit cards etc.
- Strong knowledge in mining transaction data and revealing patterns from customer spend, fee, service fee, interest income, non-interest income etc.
- 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.
- Thorough understanding of banking domain
Job Description :
- Especially in retail and payment business to measure gaps in product, price and services and also develop additional revenue enhancement opportunity for banks through extensive data exploratory analysis.
- Strong programming skills in SAS, SPSS, R and SQL.
- Some familiarity with Big Data platform is helpful but not required