Below Position is open for one of our client kindly go thorugh the JD and revert back :-
- Must have hands on expertise in developing and managing scoring models
- Work on modeling projects /unstructured problems, look at providing solutions that go beyond traditional methods - Using advanced machine learning technologies and new data sources
- Develop next-gen modeling capabilities in the team to deliver best in class predictive modeling solutions
- Must have capability to clearly communicate analyses.
- Presentations to both technical and non-technical personnel are required to be made frequently as part of the job.
- Ability to work efficiently in a matrix environment balancing between both business and functional interactions and priorities.
Education:
Masters or Doctoral degree with a specialization in Statistics, Mathematics, or other quantitative discipline
Experience:
5+ years related work experience required, with significant academic experience / contribution.
Skills:
- Strong analytical skills in conducting sophisticate analysis using bureau/vendor data, customer performance data and marketing data to solve business problems.
- Good programming skills in advanced SAS and SQL in mainframe, UNIX and PC environments.
- Advanced level expertise in statistical techniques like Regression, Logistic Regression, Factor Analysis, Segmentation, Discriminant Analysis, Stochastic Process, Time Series, etc.
- Exposure to machine learning algorithms, pattern recognition; Expertise on alternate / big data modeling techniques like Boosting / Bagging (GBM, AdaBoost), Random Forest, SVM, etc.
- Experience of working in Python, R and familiarity with Hadoop and related tools (Hive, Hue, MapReduce, Impala, etc.) preferred.
- Highly proficient in Excel/pivot tables and PowerPoint.
- Experience in BFS domain, especially in an analytics or policy role is preferred
- Knowledge on Comprehensive Capital Analysis and Review (- CCAR- ) & Dodd-Frank Act Stress Testing (- DFAST- ) regulations
- Understanding of IFRS 9, BCBS standards and its implications in consumer credit risk and PD / LGD / EAD models
Other:
- Exposure to project/process management
- Strong communication and presentation skills targeting a variety of audiences
- A qualified candidate needs to be able to work with cross functional teams
- Creates and sustains a network of strong client relationships.
- Flexibility in approach and thought process
- Ability to work effectively across portfolio risk policy teams and functional areas teams
- Strong influencing, negotiating, and facilitation skills.
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