About the Role :
- Work on various risk/marketing model development as well as creating analytical frameworks using newer alternate data for retail and corporate finance products like cards, personal loan, SBB, SME finance etc.
- Build models and tools for credit and fraud risk identification in various aspects. For example, credit risk modelling, income estimation, customer information verification,
- Analyze and conduct feature engineering for massive data such as customer profiling, e- commerce transaction, and so on and deploy the feature pipeline
- Work with tech teams to mart important data assets for continuous analytical usage
- Collaborate closely with the risk policy and business team. Translate business need and insight into machine learning models.
- Research model methodology and data mining techniques to improve model performance
Key Responsibilities :
- Experienced with data mining and feature engineering from massive raw data especially the alternative credit data
- Solid understanding and hands on experience of machine learning models such as boosting trees, regression models and good sense in feature engineering
- Good coding skill using SQL, Spark and Python
- Eager to learn new things and has passion in work
- Take responsibility, team oriented, result oriented, customer oriented and self driven
- Ensure flawless delivery of projects on tim
Qualifications :
- Post-graduation in Statistics or Economics or Quantitative Economics or Computer Science OR M.B.A. (Finance / Quantitative Methods)
- 1-5 years of relevant work experience in space of modelling and/or analytics
Role Proficiencies:
Profile of Ideal Candidate:
1) Should have the following :
a. Strong analytical & problem-solving skill
b. Detailed oriented, thorough in data understanding, pre-processing steps
c. Good statistical knowledge
d. Prior Knowledge in credit risk score development a plus
e. High level of motivation
2) Should be proficient in the following analytical areas:-
a. Predictive model development
b. Logistic/Linear Regression, Clustering, D-tree, Feature Selection, PCA
c. SVM, Random Forest, Gradient Boost,
d. Strong in Python, SAS, SQL
About Axis
Incorporated in 1994, Axis Bank is one of India's most trusted banks & the third largest in the private sector. At Axis Bank, customer centricity has always been the foundation of our business. Our efforts to address the requirements of a diverse customer cross-section are powered by robust infrastructure, advanced technology, a comprehensive monitoring & control framework & a large talent pool.
The Bank has a young & engaged workforce of over 70,000 employees, with an average age of 30 years. We are an equal opportunity employer & believe in empowering our employees by offering rich roles, learning opportunities & flexibility to chart their career, their way.
Salary offered: 12-29LPA
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