Summary:

An investment firm needed to process high-velocity market data and analyze thousands of financial documents daily. Manual research was too slow and limited the team's ability to respond to market opportunities

What We Delivered:

• Predictive Analytics Engine for stock ranking and trend analysis

• NLP Financial Text Analysis for news, earnings transcripts, and analyst reports

• Real-time Data Pipeline for stock prices, trading volumes, and macroeconomic indicators

• Portfolio Optimization Model using machine learning 

  
  

Business Outcomes:

• 45% faster research time

• 18% improvement in portfolio performance

• 80% time savings on sentiment analysis

• Ability to process 10x more data with the same team size

  
  

Tech Stack:

• Python

• Apache Spark

• Azure Synapse

• BERT/GPT

• Power BI