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20/09 Martin Chakpram
Head - Recruitment at People Realm Recruitment Services

Views:6861 Applications:432 Rec. Actions:Recruiter Actions:431

Vice President - Analytics - Machine Learning Modeling - Credit Card (10-18 yrs)

Bangalore Job Code: 745957

VP - Credit Card Analytics - Machine Learning Modeling

A global Finance firm is currently looking for a Senior Candidate to run and set up a highly specialized team to develop and prototype early-stage solutions, design and evaluate predictive models and advanced algorithms to drive business decisions for their Credit Card business, these models and solutions will be Machine Learning driven and will have to be developed from scratch.

Job Summary & Responsibilities :

1. Rapidly prototype early-stage solutions, design and evaluate predictive models and advanced algorithms to drive business decisions throughout the customer lifecycle.

2. Understand the systems and the business processes that populate those systems with data

3. Carry out data processing including statistical analysis, variable selection, and dimensionality reduction, custom attribute engineering, as well as the evaluation of new data sources

4. Leverage methods from diverse disciplines such as traditional modeling, machine learning, deep learning, artificial intelligence, statistical modelling, information theory, information retrieval and other areas to gain customer insights, draw conclusions and implement them with business partners

5. Partner with technology to implement models/algorithms in production

6. Understand finance, banking regulation and performance metrics including ROE and ROA

7. Create mathematical models of financial instruments including structured products to conduct valuation and to compute risk metrics

8. Document your assumptions and methodologies, as well as carry out validation and testing to facilitate peer reviews and independent model validation

9. Think strategically proposing new business metrics or suggesting alternatives, creating highly interpretive models that imply new context and new semantics for data

Basic Qualifications :

1. Bachelors /Masters or PhD in a quantitative field - Applied Mathematics, Physics, Engineering, Computer Science, Statistics, Econometrics and other Quantitative fields

2. Quantitative background including an understanding of data science, probability and statistics

3. Strong programming background in compiled or scripting languages (C/C++, Python, R, Java)

4. Ability to explain complex models and analysis to diverse audience

Preferred Qualifications :

1. Experience in Consumer Lending, developing Underwriting, Collections or Marketing models

2. Familiarity with advanced ML models - neural networks (feed forward, CNNs, RNNs, LSTM), Hidden Markov Models, random forests, SVMs, multivariate analysis, clustering, dimensionality reduction or participation in Kaggle data science competitions

3. Experience with distributed computing (Hadoop, Spark)

Women-friendly workplace:

Maternity and Paternity Benefits

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