Prashant Srivastava

Research interest

Machine Learning, Deep Learning, Image Analysis, NLP, Time Series Analysis

Academic background


Master's Thesis
Dept. of Computer Science, Royal Holloway
University of London

Statistical risk methods in financial markets.

  • EWMA and GARCH Volatility models.
  • Monte-Carlo and Historical simulations.
  • Basel Committee on Banking Supervision models including Expected
    Shortfall and Value at Risk.

Master's Thesis
Dept. of Physics, Indian Institute of Science
Education and Research, Kolkata

Extraordinary transmission in silicon-based micro-meter wire grid

  • FDTD simulations.
  • Quarter and half waveplates in Terahertz region.
2018 - 2020

MSc Data Science and Analytics
Royal Holloway, University of London

Field(s) of study

  • Principles of Computation and Programming : 97/100
  • Programming for Data Analysis : 89/100
  • Individual Project : 82/100
  • Deep Learning : 76/100
  • Data Analysis: 76/100
  • Machine Learning: 75/100

Grade Average: 78.3/100, Pass with Distinction


Integrated B.S.-M.S.
Indian Institute of Science Education and Research, Kolkata (Nature Index rank 9 in India)

Field(s) of study

  • Physics



  • Programming in Python (numpy, scipy, pandas, matplotlib, seaborn, scikit-learn, tensorflow, keras, mlflow).
  • Library development in Python (
  • Programming in R, C++ and MATLAB.
  • State-of-the-art machine learning technologies (CNN, RNN, GAN, NLP,
  • Web development (HTML, CSS, JavaScript, PHP).
  • Distributed/Cloud computing (PySpark, Microsoft Azure).
  • Database systems (SQL, PostgreSQL, NoSQL)
  • Latex, Git, Bash

Education and Work Experience

2020 -

Research Assistant
University Rostock, Germany

2019 - 2020

Data Scientist
London, United Kingdom, Elevate Credit International Limited

Built and implemented machine learning pipelines to support business
strategies and automate processes.

Projects: Open Banking Data, Fraud Detection, Credit Risk.


  • Reduced company’s operation costs by automating underwriting
    manual processes.
  • Prevented fraudulent applications by 80%.
  • Developed a time series credit scoring model.

Teaching Assistant
Indian Institute of Science Education and Research, Kolkata

  • Teacher for scientific programming in Python.
  • Tutored a batch of 200 M.S. students.