Associate/Sr. Associate/ Principal Associate-Model Risk Management (ExP: 3-15 years)

Location: Bengaluru
Discipline: Data Modelling, Credit Risk, Data Science/Machine Learning, Analytics , Model Governance
Job type: Permanent
Contact name: Crescendo Global

Contact email:
Job ref: 37582
Published: 10 months ago

Associate/Sr. Associate/ Principal Associate-Model Risk Management (ExP: 3-15 years)

We are looking for an experienced professional with hands-on experience in developing and implementing state-of-the-art quant/stats models. We are looking for someone with strong experience in Python, or R.

If this sounds exciting, apply with us!

Location: Bangalore

Your Future Employer:

An American bank holding company specializing in credit cardsauto loans, banking, and savings accounts, headquartered in McLean, Virginia with operations primarily in the United States. It is on the list of largest banks in the United States and has developed a reputation for being a technology-focused bank.


  • 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 to the best decisions, not just avoid the worst ones.

  • Building and validating statistical and machine learning models through all phases of development, from design through training, evaluation and implementation

  • Developing 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 system sto 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

  • Building upon the existing machine learning and statistical tool set-both by learning new technologies and by building custom software tools for data exploration, model performance evaluation, and more


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

  • Experience in Python or R

  • 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

Reach Us:

If you think this role is aligned with your career, kindly write me an email along with your updated CV at for a confidential discussion on the role.