Anuj Gopal

Anuj Gopal

ABOUT ME
Machine Learning| Financial Risk| Econometrics
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
3 years experience
3 years experience
3 years experience
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
R
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Python
SQL
R
Machine learning
Statistics
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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
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Machine learning
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