Associate/Vice President - Data Scientist - Corporate Quantitative Analytics Function - BFSI

Associate/Vice President - Data Scientist

- The role is for a Data Scientist within the Corporate quantitative analytics function, which provides data analytics expertise for corporate functions across Global Finance, Corporate Treasury, Risk Management, Human Resources,

- Compliance, Legal, and all functions within the Corporate Administrative Office (CAO). The Corporate data science team will craft analytical solutions to meaningful problems in the - corporate functions through the application of statistical and machine learning techniques.

- The Data Scientist in Bangalore will be part of a globally distributed team, with data science and engineering partners in New York and EMEA.

- He/she will help build robust and scalable solutions for various banking domains, and also enable the services to be deployed and integrated into existing business workflow. This is an exciting opportunity to work on data driven analytical solutions and have a profound influence on the business processes of a leading global bank.

Key Requirements of the Role:

- Strong understanding of Math, Statistics and the theoretical foundations of Statistical & Machine Learning, Parametric and Non-parametric models, Regression.

- Strong understanding of advanced data mining techniques, curating, processing and transforming data to produce sound datasets.

- Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop

- Experience in analyzing complex problems and translating it into an analytical approach.

- Experience in Supervised and Unsupervised Machine Learning including Classification, Forecasting, Anomaly detection, Pattern detection, Text Mining, using a variety of techniques such as Decision trees, Time Series Analysis, Bagging and Boosting algorithms, Neural Networks, Deep Learning.

- Experience with analytical programming languages, tools, and libraries (Python ecosystem preferred, but R will be considered)

- Experience in SQL and relational databases and Big Data technologies e.g. Spark/Hadoop/H2O

- Good understanding of programming best practices and building for re-use

Additional Preferred Skillsets:

- Distributed Computing and Algorithm Optimization

- Deep Learning with Tensorflow, GPU

- Financial Engineering knowledge and familiarity with risk and regulatory data

- Product mindset