ML hands on experience  – Should have hands on experience of working on ML projects end to end. Good understanding of machine learning libraries in python, py-spark like MLlib, Scikit learn etc. People with prior experience of working advanced ML techniques like – GBM, X-G boost are required. Banking Experience –  Should have sound understanding of banking terminologies from risk and operations side. People with prior experience with collections models/strategy are preferred. People worked in US banking with MRMG requirements is necessary. Data Wrangling – Should be comfortable with data fetching in SQL, python - numpy, pandas, matplotlib and Py-Spark etc. from Hadoop and SQL server. Ability to work with the large data-sets in an efficient manner. Should have a knack to take care of the quality of data prepared. Basic Statistics and ML knowledge – Should have conceptual understanding of basic statistical topics and should be aware of advanced ML models evaluation techniques. People with prior experience in production ready models are preferable.