Nalini Bhadouria is a data scientist with over 3 years of experience in credit risk modeling, machine learning, and data analysis. She has worked on developing application scorecards using logistic regression and cost-sensitive learning algorithms to assess creditworthiness. She also optimized an SMS parsing model to reduce execution time and extract customer income from SMS data. Nalini has a dual degree in IT from Indian Institute of Information Technology and skills in Python, AWS, and analytical tools like KNIME and Tableau.

1. Nalini Bhadouria
Data Scientist
Fintech | Data Science | Research oriented
nalini.com7@gmail.com
91-7773849557
Pune, India
SKILLS
credit risk Model
development
Feature engineering
Data mining
Machine learning
algorithms
Data Analysis
TECHNICAL
SKILLS
Operating System :
Linux,Windows
Visualization : Tableau
Languages :
Python,C,MATLAB
Analytical tool: KNIME, MS
Excel
Databases :
MySQL,PostgreSQL,
MongoDB
Production Skills : Python
Flask framework, NGINX
server, Docker, AWS
lambda function,AWS
sagemaker
WORK EXPERIENCE
07/2018 – Present
Data Scientist
EarlySalary [Social Worth Technologies]
Pune
EarlySalary is a mobile app which offers banquet of products tailor to need of young India including instant cash loans,shopping
loans, interest free EMI options and a line of credit to shop. The company conducts prudent risk assessment by leveraging
machine learning to go beyond traditional underwriting.
Developed a new version of application scorecards using cost-sensitive learning algorithm and logistic
regression to determine credit worthiness of young professionals with poor credit history.
Involved in model development, model maintenance,monitoring and deployment.
Involved in data cleaning, development of data repository, feature creation and feature engineering.
Provided support in research orientated activities associated with models,optimization of algorithms to
reduce execution time, analytical tools like KNIME and Python and some AWS services.
PROJECTS
1. Application scorecard for new-to-credit/poor credit history customers. (12/2018 – 02/2019)
The objective was to build an application scorecard that can be integrated in underwriting process of loan applications.
Developed credit risk model for new to credit customers, that helps the company to maximize profits and asset growth
while reducing the credit and operating loss risk. I was involved in end-to-end development and deployment process.
Achievement- With this new scorecard, the approval rate of customers got increased by 12% and delinquency
percentage dropped by 8 %.
2. SMS Parsing model optimization and deployment (07/2018 – 09/2019)
The objective was to enhance and optimize the SMS categorization model which labels each SMS based on the text of
that SMS like banking,credit card,shopping,insurance etc and to extract customer's income from his/her SMSes.
Achievement- Real time execution time got dropped from 14 sec to 2 sec for each customer having around 8000 SMSes.
EDUCATION
07/2013 – 05/2018
Dual Degree [B.Tech+M.tech] in information technology
Indian Institute of Information Technology, Gwalior
CGPA - 7.30
M.TECH Thesis Project- Analysis of cellphone
radiation on brain cell images using Image
Processing Techniques.
B.TECH Thesis Project- Forensics analysis of cloud
artifacts.
CONFERENCES & COURSES
1. Machine Learning by Stanford University, Coursera (12/2015 – 05/2016)
Authorized by Standford University and offered through coursera
2. IEEE 2018 1st International Conference on Multimedia Analysis and Pattern Recognition (MAPR)
(04/2018)
Nissl Stained Rat Brain Cell Image Analysis Post Exposure to Electromagnetic Fields Using Image Processing Techniques.
ACHIEVEMENTS
1. IIT Advanced 2013 Rank 12242 and JEE-Mains-2013 Rank 19301
2. Got selected for INSPIRE scholarship.
3. Secured 88th position in National Chemistry Olympiad.(2009) and Got meritorious position in
TSI (Talent Search Institute) General Knowledge Competition & Mathematics Olympiad.
Achievements/Tasks
Courses