Manager - Model Development + Deployment - Financial Services

- You'll be required to have advanced analytics to optimise processes, and identify and anticipate risks across financial (credit, market risk) and non-financial (compliance, behavioural, operational risk) areas.

- You'll also need knowledge in statistical computer languages (Python, R, SQL, etc.) and tools (Alteryx) to manipulate data and draw insights from large data sets and knowledge of a variety of machine learning techniques (clustering, decision tree learning, text mining, NLP, Ensemble Learning, Gradient Boosters, Neural Networks, Social Network Analysis etc.) and their real-world advantages/drawbacks.

- You'll also bring knowledge in advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.

- You should have experience in deploying and productionising ML models/Python scripts on the cloud and managing end to end life cycle of the same as well as developing CI/CD principles and maintaining CI/CD tools/platforms.

- Financial services industry experience is preferred and experience using web services such as S3, Spark etc. and distributed data/computing tools such as Map/Reduce, Hadoop, Hive, Impala and similar will be an added advantage