Data Scientist

Job Responsibilities 
Utilize data analytics and advanced statistical techniques to inform investment decision-making and drive business growth.
Collaborate with cross-functional teams to identify opportunities for leveraging data to enhance investment strategies.
Develop and maintain a robust data infrastructure to support data-driven decision-making.
Stay updated on industry trends and best practices in data science and investments, and implement new techniques and tools as needed.
Lead the development and implementation of advanced data modelling and predictive analytics to support investment strategies.
Oversee the creation and maintenance of data dashboards and reports to track investment performance and identify areas for improvement.
Primary Skills: Has experience with data science, statistical modelling and time series analysis of financial markets data, Fixed Income Assets, Investment Banking.
Secondary Skills : Has experience in Gen AI , Language Model etc.
Required Education
Bachelor’s degree in computer science or a related field.
Proficiency in the mathematics underlying Machine Learning
Ability to present complex technical information in a clear and concise manner to a variety of audiences.
Required Experience
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 modelling 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.)
Exposure to creation of data pipelines to engineer apps deployment (CI/CD) across platforms and environments and working with ML pipelines