Data Science in Finance

About the Expert:

Neelotpal Shukla is Quantative Research Manager at Morningstar. He has a Master's Degree from internationally acclaimed University of Illinois focusing on extensive scientific research. He is also an alumnus of Indian Institute of Technology Madras. 

Neelotpal has experience in factor investing, risk modelling, portfolio construction, probabilistic modelling, computational engineering, advanced data analysis, and uncertainty quantification. 

About the Session:

Data scientists play an essential role in the finance business, whether it's fraud detection, risk management, or assisting banks in navigating a recession. They can help organizations avoid financial disasters and instead focus on economic opportunities.

Finance, more than any other business, recognizes the value of data scientists. Financial firms saw a need for analytical, curious, and solution-oriented individuals who could wrangle massive amounts of consumer and financial data for statistical analysis, forecasting, and risk analysis long before data science was even a recognized industry term. 

With an increasing proportion of transactions now taking place online and startling volumes of financial data being generated every day, there is no shortage of opportunities for data scientists—especially those who like playing with numbers.

In this live interactive online learning session, Neelotpal will discuss:

• How is data science used in finance?

• Key Requirements for the Data Science Team. What software, tools, and techniques does the team use regularly?

• How does Data Science impact the company numbers?

• Where to start learning data science for finance?

Session Format: