Data Scientist - Machine Learning/Deep Learning - Asset Class Industry

A highly challenging role where you will be a part of a Vision-Led team that is a Leading Asset management or Investment firm. You will be extensively involved in developing technology related to Artificial Intelligence and Machine Learning. Hence, a highly exciting opportunity for those with excellent understanding of algorithms so you can drive your passion to solve business problems and excel in your career as a Data Scientist!

Location: Mumbai

Your Future Employer:

A leading, global group with billions of assets under management providing comprehensive financial services serving millions of customers.

Responsibilities:

- Developing Models on ML.

- Collecting and integrating data from various data sources to be used for building the models (writing crawlers, connecting to databases for extracting data for training algorithms, creating features that support hypothesis.)

- Training and Testing different ML/DL algorithms, performing iterative experiments with different techniques to discover the best performing algorithm.

- Creating frameworks to monitor algorithm performance.

- Work with internal and external teams to develop models (ranging from data exploration to feature engineering and model development to validation and scoring.) and put them into production

Requirements:

- Experience in machine learning in Asset management/investment domain.

- Excellent skills in either Python or R. Should be comfortable with command-line tools.

- Excellent in forecasting methods like simple exponential smoothing, multiplicative seasonal indexes, simple and weighted moving averages and time series forecasting methods.

- Exposure to with advanced deep learning techniques such as LSTM. CNN, Dense neural networks.

- Good SQL expertise.

- Should have at-least 1 end-to-end ML project experience.

What is in it for you:

- An opportunity to work with a blue- chip firm in a high visibility role as a part of lean team.

- Work in a dynamic environment for an established brand.