Business Analyst/Data Scientist - IITs/BITS Pilani/DSE/ISI

Business Analyst / Data Scientist position for an American Bank, for Bangalore location.

We are looking for :

Education Criteria - Only Tier1 campuses - Top 6 IITs, BITS Pilani, DSE, ISI Kolkata, Top 3 IIMs.

Exp.: 2- 6 years in banking or any financial companies

Also the candidate must have worked on:

1) Model risk management

2) Credit risk analysis

3) Machine learning

4) Done codding in python

5) Regression

6) Market research

Interested candidates, please share your updated CV or WhatsApp at 9230061391

Role Description:

In this role you will:

- Partner cross-functionally with data scientists, quantitative analysts, business analysts, software engineers, and project managers to manage the risk and uncertainty inherent in statistical and machine learning models in order to lead Capital One to the best decisions, not just avoid the worst ones.Build and validate statistical and machine learning models through all phases of development, from design through training, evaluation and implementation

- Develop new ways of identifying weak spots in model predictions earlier and with more confidence than the best available methods

- Assess, challenge, and at times defend state-of-the-art decision-making systems to internal and regulatory partners

- Leverage a broad stack of technologies - Python, R, Conda, AWS, and more - to reveal the insights hidden within huge volumes of data

- Build upon your existing machine learning and statistical toolset - both by learning new technologies and by building custom software tools for data exploration, model performance evaluation, and more

- Communicate technical subject matter clearly and concisely to individuals from various backgrounds both verbally and through written communication; prepare presentations of complex technical concepts and research results to non-specialist audiences and senior management

- Flex your interpersonal skills to translate the complexity of your work into tangible business goals, and challenge model developers to advance their modeling, data, and analytic capabilities