Data Scientist

Responsibilities:

•Primary Skills : Has experience with data science, statistical modeling and time series analysis of financial markets data, Fixed Income Assets, Investment Banking.

•Secondary Skills : Has experience in Gen AI , Language Model etc.

•       Bachelor’s degree in computer science or a related field.

•       Competencies typically acquired through an advanced degree (in Statistics, Mathematics, Data Science or other relevant field of study)

•       Proficiency in the mathematics underlying Machine Learning

•       Ability to present complex technical information in a clear and concise manner to a variety of audiences.

•       Minimum 14+ years of experience in data science designing and deploying statistical modelling with at least 6 years of hands-on experience in Financial/Investment / Asset Management / Fixed Income.

•       Has experience with data science, statistical modeling and time series analysis of financial markets data, Fixed Income Assets and/or Investment Banking.

•       Has experience in Gen AI , Language Model etc.

•       Worked for asset management firms in roles aligned to the front office.

•       Has advanced knowledge of python and/or R

•       Asset Allocation, Research, quat engineering

•       Broad experience with hands-on modelling and DS lifecycle activities, particularly in Python, and ability to communicate at a high level with DS and non-technical leaders

•       Knowledge of graphical packages such as plotly or gg plot

•       Excellent understanding of Statistical modeling, Machine Learning (Supervised, Unsupervised, Recommendation engines, Optimization etc.)  Deep Learning (RNN, CNN, LSTM, Auto encoders, GANS etc.), Natural Language Processing techniques and algorithms

•       Strong coding experience in Python, Pyspark, Keras/tensorflow

•       Experience with SQL & at least one NoSQL databases

•       Experience of working on any of cloud platform (AWS, Azure, IBM etc.)

•       Work closely with data engineers to source, analyze and engineer features, collaborate with fellow data scientists to develop, test and deploy Machine Learning models

•       Exposure to creation of data pipelines to engineer apps deployment (CI/CD) across platforms and environments and working with ML pipelines

•       Demonstrate analytical and problem-solving skills, particularly those that apply to the big data environment