Anuj Gopal

ABOUT ME

Machine Learning| Financial Risk| Econometrics

Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making.

I have an experience of working in R,Python,SAS and SQL environment to visualise the random data into meaningful informations. I have a knowledge of predictive Modelling, Data mining and Big Data as well. During the projects, I have also worked on Hadoop environment and used Hive, Apache Spark to examine the Big Data provided to us.

English

New Delhi (+05:30)

Joined July 2019

EXPERTISE

Machine learning

3 years experience

Shiny

3 years experience

SOCIAL PRESENCE

GitHub

K-Anonymity

Python code for K-Anonymity data privacy algorithm

Python

Stack Overflow

1 Reputation

EMPLOYMENTS

Analyst

HSBC

2017-07-01-2019-08-01

At HSBC, my job was to write algorithm to cope up with money laundering activities inside HSBC. Using SAS and python as the programming l...

At HSBC, my job was to write algorithm to cope up with money laundering activities inside HSBC. Using SAS and python as the programming language, I was successful in implementing models to optimise alert generation of suspicious activities as well as minimising the alert volume in order to keep a check on cost incurred during the whole process.

Python

SQL

Python

SQL

Machine learning

Statistics

PROJECTS

Credit Ratings Modeling

2016

-Built a regression model to predict Days past due of a customer given the historical transactions, to gain valuable insights regarding c...

-Built a regression model to predict Days past due of a customer given the historical transactions, to gain valuable insights regarding credit worthiness -Wrote an algorithm in R, to extract village name from the address of a customer using for-loops and parallel computation -Income estimation: Using loops in R and python, derived variables related to credit card and EMI loan transactions to estimate the income of a customer -Also, validated the existing credit rating model using linear regression; came up with weights and percentage error associated with each of the derived variables

Machine learning