• Model Development and Validation:


• Role requires use statistical techniques to build models for credit and market analytics.


• The objective of these models would be to help banks & investment companies evaluate risk in their current portfolio or in potential investment opportunities.


• Models/ scorecards will be developed on company financials, industry or market data. Other data sources might also be used based in case required.


• Model development would involve use of technique such as logistic regression, clustering, segmentation, forecasting. Knowledge of machine learning mechanisms is optional but would be preferred.


• Ensure high model accuracy as well as stability via thorough back-testing and validation of model

• Model Implementation:


• Generate scores or output of the model are share with relevant stakeholder (which can be a client or business team)


• Help various stakeholders understand implications of the model and develop use cases for the same


• Liaison with technology team to automate generation of model output


• Process Adherence:


• Ensure high quality of analysis and research output


• Monitoring models through MIS


• Proper documentation of model development & validation processes


• Successfully meeting deliverables and client requirements


• Initiatives for productivity improvement

Required Skills:

• Educational Qualifications: A post graduate (M.A/M.Sc/MBA) in finance, stats or economics or any other quantitative discipline with an exposure to finance


• 2-4 years of related experience


• Strong quantitative aptitude & business analysis skills


• Understanding of econometric and statistical concepts like hypothesis testing, linear regression, LDV models (logit/probit), time series.


• Programming expertise, especially in R, SAS or SQL.


• Good MS-Office skills, especially in Excel


• Excellent oral, written communication and presentation skills


• Detailed oriented & organized

Preferred Skills (Optional):

• Familiarity with quantitative investment approaches and financial markets


• Understanding of credit or market risk frameworks such as Probability of Default, LGD, Value at Risk etc


• Experience with programming tools such as Python or Hadoop


• Strong background in modeling with large amounts of data