Raj Kumar Singh

Associate Consultant

Mumbai, Maharashtra, India6 yrs 4 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Machine learning enthusiast with practical experience.
Improved predictive model performance significantly.
Strong foundation in quantitative research and finance.

Stackforce AI infers this person is a Fintech professional with strong quantitative research and machine learning expertise.

Contact

Skills

Core Skills

Machine LearningData Science

Other Skills

CC++Case StudiesData AnalysisManagementMicrosoft ExcelMicrosoft OfficePythonStatistics

About

I am currently working in Quantitative Research team as an Associate at JPMorgan Chase & Co. working for security services team. I have graduated from IIT Kharagpur and have cleared CFA level 1 and level 2. I am a machine learning enthusiast along with having alot of interest in the field of Finance, I have done multiple projects involving the same in my job, internships and in my college.

Experience

Jpmorgan chase & co.

3 roles

Quantitative Research Associate

Jan 2024 – Present · 2 yrs 2 mos · Mumbai, Maharashtra, India

Quantitative Research Analyst

Jul 2021 – Jan 2024 · 2 yrs 6 mos · Mumbai, Maharashtra, India

Quantitative Research Summer Analyst

May 2020 – Jul 2020 · 2 mos

Worked with security services team on a binary classification XGBoost model to predict whether a trade would settle within the contractual settlement date and improved the model performance from 45% to 55% F1-score and reduced the computational time by around a millisecond per trade using exploratory data analysis and feature engineering.

Machine LearningData AnalysisStatistics

Slicepay

Data Science Intern

May 2019 – Jul 2019 · 2 mos · Bengaluru, Karnataka, India

Used Google Maps API to find the user’s location and made location based features to add those features in the existing boosted model to predict user's days past due to increase the model performance from 73% to 81% F1- score.
Clustered regions based on default rate in last one year and build a model that gives an alert if an application comes from a risky area which helped the company to prevent 16 probable fraud attacks made from July 2019 to June 2020.

Data ScienceMachine LearningData Analysis