Work with a Leading Banks Risk Management team on specific projects/requirements pertaining to risk Models in
consumer and wholesale banking
Enhance Machine Learning Models using PySpark or Scala
Work with Data Scientists to Build ML Models based on Business Requirements and Follow ML Cycle to Deploy them all
the way to Production Environment
Participate Feature Engineering, Training Models, Scoring and retraining
Architect Data Pipeline and Automate Data Ingestion and Model Jobs
Skills and competencies Required:
Strong analytical skills in conducting sophisticated statistical analysis using bureau/vendor data, customer performance
Data and macro-economic data to solve business problems.
Working experience in languages PySpark & Scala to develop code to validate and implement models and codes in
Credit Risk/Banking
Experience with distributed systems such as Hadoop/MapReduce, Spark, streaming data processing, cloud architecture.
Familiarity with machine learning frameworks and libraries (like scikit-learn, SparkML, tensorflow, pytorch etc.
Experience in systems integration, web services, batch processing
Experience in migrating codes to PySpark/Scala is big Plus
The ability to act as liaison conveying information needs of the business to IT and data constraints to the business applies equal conveyance regarding business strategy and IT strategy, business processes and work flow
Flexibility in approach and thought process
Attitude to learn and comprehend the periodical changes in the regulatory requirement as per FED