Senior Associate - Model Risk Management - BFS

Only from IIM (A,B,C,D); IIT (Kharagpur, Delhi, Chennai, Roorkee) and BITS Pilani

You'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

In DataLabs Model Risk Management team, we defend the company against model failures and find new ways of making better decisions with models. We use our statistics, software engineering, and business expertise to drive the best outcomes in both Risk Management and the Enterprise. We also understand that we can't prepare for tomorrow by focusing on today, so we invest in the future: investing in new skills, building better tools, and maintaining a network of trusted partners. We learn from past mistakes and develop increasingly powerful techniques to avoid their repetition.

The ideal candidate is :

- Inquisitive. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea.

- Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.

- Statistically-minded. You've built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, time series, and deep learning.

- Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.

- Degree in statistics, math, engineering, economics, econometrics, financial engineering, finance, or operations research with a quantitative emphasis preferred

- Proficiency in key econometric and statistical techniques (such as predictive modeling, logistic regression, survival analysis, panel data models, decision trees, machine learning methods)

- 2+ years of experience model development or validation

- 2+ years of experience in R or Python for large scale data analysis

- 2+ years of experience with relational databases and SQL

- Experience in Financial Risk across any area or Financial Risk Management (FRM) certification