Navendu Tripathi

Navendu Tripathi

Navendu Tripathi

Experienced Professional in Risk Management (Credit Risk Modeling/ Market Risk/Data Analysis) and a recent graduate in Quantitative Finance with a good Programming Skills.

@navendu

Joined Sep 2020

Hyattsville, MD, USA

About

I have spent nearly 4 years doing number crunching and risk management for a banking and finance business, and I am keen to continue developing a career in the field of risk analytics and Data science. I have a sound data analysis experience in a bank where I was performing analysis, research, model development, implementation, testing & verification, documentation, presentation & reporting to senior executives.

 I have good knowledge in Excel, R, Python, SAS, Machine learning, SQL query, and data-driven optimization are the rhythm of the drumbeat I march to. As much as I’m into data manipulation, it’s the analysis of data that really gets me going. I like to explore the relationships between numbers and translate digits and spreadsheets into stories. In the age of big data, these stories become actionable solutions and strategies for businesses, and I take pride in my ability to make data accessible to decision-makers. On a personal level, I am detail-oriented, organized, and precise in my work; the only thing cleaner than my room are my spreadsheets. 

I have strong communication skills with a knack for clear and illuminating presentation. I’m comfortable on my own facing the numbers, but I really enjoy being part of a motivated team of smart people.

Experiences

4yrs 11mos

Graduate Research Assistant

Jan 2019 - May 2020

1yr 3mos

Jan 2019 - May 2020

1yr 3mos

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•Created & Graded assignments which included practical data experience, using computational tools to solve economic models numerically, programming econometrics methods, and presenting empirical results for 85+ graduate students by using R, Python & SAS. • Assisted Professor Michael Padhi with teaching materials and supported students with tutoring classes related to risk management & bank management topics.
Python

Python

R

R

Tableau

Tableau

Quantitative Risk Analyst Extern

Mar 2020 - May 2020

1mo

Mar 2020 - May 2020

1mo

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•Extracted & manipulated large data set of 500,000 transactions of Treasury Securities, Agency Securities, Mortgage Backed Securities, and Corporate securities from the Federal Reserve Bank of Newyork to estimating a statistical scorecard of securities settlement failures and discovered potential predictive factors for when firms are less likely to deliver security during a short transaction. • Developed Machine learning model using gradient boosted decision trees and random forest to conduct anomaly detection, information filtering, and securities settlement failure prediction on large datasets of 500,000 settlement transactions by using SAS & Python. • Performed research on a previously untouched subject within finance and risk management.
Python

Python

Credit Research Analyst

Jan 2020 - Jan 2020

Jan 2020 - Jan 2020

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Developed and cleaned 100,000+ Mortgage loan level data set with 20+ risk factors tracked over 60+ quarters in Python. • Reviewed profile and performance of 100,000+ Mortgage loan populations over the past year and compiled information and analysis for company wide use through advanced econometrics and regression modeling. • Analyzed the severity of credit risk from predetermined loan populations through credit risk models PD, LGD and EAD; researched and presented possible solutions to senior authority to reduce risk.
Python

Python

Tableau

Tableau

Credit Risk Analyst

May 2015 - Dec 2015

7mos

May 2015 - Dec 2015

7mos

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• Successfully implemented the framework of Behavior Score in SAS and SQL from the current one in Excel, to monitor the payment patterns of customers of both Secured and Unsecured loans, that reduced the time of score calculation by 70%. • Maintained, run and improved PD, LGD & EAD credit risk models of 1 million mortgage loan to predict the losses on loans by using SAS & Python. • Generated 400 different paths of unemployment, mortgage, and interest rates by building stochastic models. • Simulated the loss distribution of a 20K+ loans over 500 paths for 70 quarters in Python and SAS. • Conceptualized and created an Early Warning Signals (EWS) system to identify accounts/customers that might potentially default in future, using a combination of parameters like CIBIL Score(FICO), Behavior Score, Credit Risk Rating, Collateral Valuation, On-ground feedback, market news, etc, and suggested corrective measures for 110,000 accounts/customers by using Python & SAS.
Python

Python

MySQL

MySQL

R

R

Tech Stack

Languages
Python

Python

Junior

R

R

Junior

Business Intelligence
Tableau

Tableau

Junior

Databases
MySQL

MySQL

Beginner

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