With over 10 years of comprehensive experience in Data Engineering, Data Science, and Data Analytics, I have primarily worked with major financial clients, including Morgan Stanley, Fannie Mae, and Barclays, alongside other global leaders like Corevitas and Walmart. I have a proven track record of leading impactful projects and providing effective mentorship.
Quantitative Researcher by JP Morgan Chase
Below are few sample projects highlighting my expertise in Data Engineering, Data Science, Data Analysis, Databases, Generative Artificial Intelligence, LLMs, SQL, Python, Power BI, Tableau and Machine & Deep Learning.
Engineered a Python & Streamlit application, leveraging Google Gemini Pro AI and Hugging Face, to predict personal income with a R score of 0.87 and provide tailored financial advice, boosting user decision making by 80% based on their socio-economic data.
Built a Netflix like movie recommendations system with a self-created dataset with over 1 million movies across 42 features, offering tailored recommendations through a combination of multiple criteria, hybrid and customized filters.
Developed a Power BI and Deneb – based intelligence dashboard integrating Spotify API for real-time music streaming insights, crafted and monitored 6 essential KPI’s to analyze trends, enhancing strategic marketing and artist promotion decisions.
Used multiple machine learning models to forecast sales (retail store) and performed time series analysis.
Developed a ML model to give various recommendations of financial products & services on target customer groups.
Developed an interactive Tableau dashboard to monitor sales and profit metrics, featuring dynamic exploration of 20+ KPIs. This facilitated a 20.4% increase in year-over-year sales and improved decision-making in resource allocation.
Below are the details to reach out to me!
Available for opportunities wherever needed