Axis Bank - Head - Model Engineering

Job Description :

The candidate will be leading the Model Engineering wing under the Data Science umbrella and will be primarily responsible for developing state-of-the-art AI capabilities for the bank

The candidate would be responsible for :

- Leading the development of predictive models using latest machine learning / statistical methods on big-data platform

- Keeping track of latest developments in the machine learning world and drive POCs to provide value-based solutioning for the bank

- Introduce newer methodology in model development & implementation

- Working with vendors to gain industry-knowledge and develop in-house capabilities

Key Result Areas :

1. Enhance current suite of Convolutional Neural Network models - focused on identifying/predicting customer churn and product propensity

2. Build a 'Deep Learning Workbench' with the- right analytical tools- - Python/TensorFlow,- high performance hardware- like GPU and- right data architecture- - like usage of MongoDb-

3. Research and build new algorithms to improve the current high standards of credit risk predictions

4. Standardize the usage of latest data processing methods for faster development and implementation of models in the larger data science team

5. Train and mentor a group of data scientist in a 200+ member analytics group

Key Relationships People Manager :

Competencies Required "- Subject matter expert in statistical techniques with good exposure in the field of machine learning

- Excellent analytical and problem solving cabability

- Ability to guide / mentor junior analyst to deliver on complex analytical projects

- Well conversant with Hadoop, SQL, Oracle

- Strong project management and stakeholder management skills

- Strong communication & presentation skills

Academic Qualifications Required

PH.D / Post graduation in Statistics or Quantitative Economics or Computer Science

Nature of Relevant Work Experience Required "- Predictive model development

- Logistic/Linear Regression, Clustering, D-tree, Feature Selection, PCA

- Artificial Neural Network (Deep Learning), SVM, Random Forest

- Python, Tensorflow, Scikit

- SAS, R

No. of Years of Relevant Work Experience - Candidate is required to have 5-8 years of relevant work experience in statistical modeling with focus on machine learning techniques. The candidate must have project-related experience in working on "High Performance" environments / platforms like BIG-DATA, Hadoop etc...; should be self-driven and passionate about the field of machine learning; should have the ability to liaise with multiple stakeholders and get the execution done smoothly.