Full-stack data science, AI & machine learning
Data science that holds up in production.
Three years building credit-underwriting and fraud models at a lending fintech, plus independent ML work and a self-built computer-science education.
72%+AUC
Risk-model performance
16%
Cohort risk reduction
200M
SMS processed a day
450%+
Fraud-detection improvement
3
Data scientists led
3 yrs
At MoneyView, Apr 2021 – Jul 2024
At MoneyView
Underwriting at scale.
As Manager, Data Scientist L3 at MoneyView (Whizdm Innovations), I built the machine-learning models behind credit underwriting and led a three-person team.
That meant a pipeline turning raw SMS data into features at 200 million SMS a day, a risk model that reached 72%+ AUC and cut risk in the targeted cohort by 16%, and a set of fraud-detection improvements that exceeded 450%.
Day-to-day tools were Python, SQL, pandas, scikit-learn, Flask, Plotly, AWS and Metabase.
Independent work
Learning in public.
Outside employment I’ve built fake-news, spam and image classifiers, GIS dashboards and automation bots. Since 2019 I’ve followed a self-built curriculum drawn from MIT 6.0001 and 6.0002, Harvard CS50 and Stanford CS229. See the education page.
Today the same skills drive the analytics and AI systems that run Puranmal Sons, from ERP-fed dashboards to a Gemini-assisted WhatsApp CRM.
Toolkit
Stack.
- Python
- SQL
- pandas
- NumPy
- scikit-learn
- Matplotlib
- Flask
- FastAPI
- Plotly
- Dash
- Jupyter
- Metabase
- AWS S3
- EC2
- Athena
- SageMaker
- Glue
- Postgres
- SQL Server
- Gemini
- Claude
Questions
Data science, answered.
What does a data scientist do in credit underwriting?
They build models that estimate how likely a borrower is to repay and how likely an application is to be fraudulent, using applicant, credit-bureau and alternative data, so lenders can approve, price or decline faster and with less risk. At MoneyView, Raghav Palriwala built these models and the data pipelines that feed them.
What did Raghav Palriwala do at MoneyView?
From April 2021 to July 2024 he was Manager, Data Scientist L3. He led a three-person team, built ML models for credit underwriting, an SMS-data pipeline processing 200 million SMS a day, a risk model with 72%+ AUC that reduced cohort risk by 16%, and fraud-detection improvements exceeding 450%.
Which tools does he use for data science?
Python, SQL, pandas, scikit-learn, Flask, Plotly and Metabase for modelling and reporting, with AWS (S3, EC2, Athena, SageMaker, Glue) for data and deployment. For newer work, he builds LLM-integrated apps with Gemini and Claude.
Can I hire him for data science or machine-learning work?
Yes, remotely and worldwide, through YourTechConsultants. Dashboards, analytics pipelines, ML models and AI-integrated tools are all in scope. Email rmpalri@gmail.com with a short brief.