Assistant Manager - Risk Modeling

Assistant Manager - Risk Modeling

Genpact
Not Specified
Not Specified

Job Description


With a startup spirit and 90,000+ curious and courageous minds, we have the expertise to go deep with the world&rsquos biggest brands&mdashand we have fun doing it. Now, we&rsquore calling all you rule-breakers and risk-takers who see the world differently and are bold enough to reinvent it.
Transformation happens here. Come, be a part of our exciting journey!
Are you the one we are looking for
Inviting applications for the role of Assistant Manager &ndash Risk Modeling!
We are looking for a seasoned risk modeling professional to lead client facing projects/engagements in quantitative model development, validation, statistical analysis, and portfolio analytics in the risk and regulatory area. This would involve application of various industry best practices and techniques in risk modeling including but not limited to linear/ logistic regression, time series methods, Markov chain, survival modelling and machine learning techniques.
In addition to working hands on as delivery lead for advanced risk analytics projects, the selected candidate would need to supervise, manage and train teams responsible for developing and/or validating retail risk and regulatory models.
Responsibilities

  • Work hands-on for critical risk modeling projects as well support team&rsquos project deliverables with statistical and domain expertise

  • Works hands-on in development, re-development and calibration of risk and regulatory models, including but not limited to credit decision scorecards, fraud and AML models, Basel IRB &ndash PD, LGD, EAD, Stress Testing and IFRS 9/CECL models

  • Modeling strategies for automated decision making

  • Providing thought leadership and oversight for a team of risk modelers/validators

  • Develop presentations to be shared with senior client management

  • Data and quantitative analysis to support modeling decisions

  • Leading development of model methodologies, algorithms and diagnostic tools for testing model robustness, sensitivity and stability

  • Detailing model techniques and interpretation of variables used in the models to be documented and presented to client Stakeholders

  • Validation for the source data quality, forecast data quality as well as change management

  • Helping develop thorough technical documents for distribution and presentation to senior management, model developers, auditors and regulators

  • Bringing in industry best practices and consultative inputs to help deliver continuous value to client engagements in advanced risk analytics

Qualifications we seek in you!
Minimum qualifications

  • Master&rsquos degree in a quantitative discipline &ndash Economics/Statistics/Mathematics/Finance etc.

  • Experience in BFS analytics, with experience in credit risk modeling

  • Excellent knowledge of various statistical techniques and proven skill in statistical modeling (Logistic Regression, GAM, Time series, Survival Techniques &ndash Competing Hazard, COX proportional hazard, Clustering, CHAID/Classification trees Etc.)

  • Good client management and communication/presentation skills &ndash written & verbal

  • Master&rsquos degree in quant discipline - Statistics/Economics/Finance/Mathematics

  • Ambitious, proactive, &ldquocan-do&rdquo attitude. Ability to work under ambiguity and with minimal direct supervision.

  • Expertise in SAS, SQL, Python

  • Hands-on experience in Machine Learning (Boosting, Bagging techniques) modeling is a plus

  • Experience in visualization technologies Tableau, Spotfire, MATLAB and SPSS is a plus

  • Knowledge on cloud technology like Azure, Devops , AWS Sagemaker and in change control software like GitHub and SVN would be preferred

  • Ability to work independently on complex projects

  • Consultative mindset and experience in client interfacing with strong interpersonal skills

  • Experience in building and leading quantitative risk analytics teams

  • Project management experience

  • Must be articulate and confident to manage senior stakeholder conversations

  • Experience with application of machine learning techniques including XG Boost, GBM, Neural Network, SVM and Random Forest preferred

Preferred qualifications

  • Excellent Communication skills

  • Self-motivated and execution oriented

  • Ability to learn very quickly and identify improvement opportunities &ndash high energy and self-starting individual


Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values diversity and inclusion, respect and integrity, customer focus, and innovation. For more information, visit . Follow us on , , , and .

About Genpact

Job Source : genpact.taleo.net

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