AVP - Advanced Analytics - Machine Learning - Banking Domain

Advanced analytics & Machine learning have found its way into application in a number of risk management functions in the banking industry. Data capture for analysis is increasingly moving towards utilizing granular on-us & off-us transaction data and non-mainstream information like social media. Conventional statistical approaches are making way for machine learning techniques in many strategic areas of application for ex in customer acquisition and account management strategy, early warning system(EWS) in collections and fraud, enhancing accuracy and stability of credit risk models, nest generation stress testing, geospatial analysis and pattern recognition for financial crime to name a few. Advanced Analytics team under Retail Risk Analytics umbrella will be an integrated team targeted towards leveragingnew age concepts like - Machine Learning- for the bank's real life business problems. This team will work across various risk analytics functions to develop enhanced capability in advanced analytics for retail risk teams and beyond.

Scope of Activity:

- Help deliver POCs from various risk sub functions by providing subject matter knowledge of advanced analytics & Machine learning techniques.

- Execute advanced analytics projects hands on in collaboration with various risk and RBWM sub functions

- Leverage Data Labs to explore and recommend new tools for usage.

- Help support trg & development of internal workforce to build a strong team of data scientist

- Monitor & liaison with the industry/academia for new methodology, tools & techniques and applications.

- Hands on experience of applying various machine learning techniques in real life problems

- Familiar with a majority of the techniques below and proven expertise in a few of them is a - MUST-

- Neural Network/ Artificial Neural Network)

- Random Forest

- Gradient Boosting

- Logit boosting

- Apriori Algorithm

- Support vector Machine

- Recommendation Learning

- Self-Organizing maps

- Pattern Recognition

- Interact effectively with a wide variety of people with varying backgrounds and responsibilities, including other credit risk analysts, project managers, operations personnel,

- Conduct training and developmental activities.

- Keep abreast with new technologies in machine learning domain

- Adhere strictly to compliance and operational risk controls in accordance with company and regulatory standards, policies and practices.

- Adhere to IT data policies, procedures and governance framework when performing tasks so as to ensure controls are in place and departmental goals are met

- Bachelor's / Master's Degree in discipline like IT/Software, Engineering, Mathematics, Statistics, Economics etc from a reputed university

- 8-12 years in the analytics industry; of which at least 5 years of experience in machine learning/ high end analytical techniques

- Should be competent with techniques like neural network, boosting, support vector machine, random forest etc (hands on experience required)

- Good organizational, project management, analytical, problem-solving and verbal/written communication skills

- Comfortable working with the onshore/offshore team

- Good Knowledge of SAS/ R programming would be highly preferred

- Demonstrated success in managing multiple deliverables concurrently often within aggressive timeframes. Ability to cope under time pressure with collaborative attitude and approach

- Exposure to banking domain would be preferred