A

Apoorv Vats

About

Detail

Maharashtra, India

Timeline

work
Job

Résumé

Jobs verified_user 0% verified
  • Databricks
    Finance Data Analyst
    Databricks
    Aug 2024 - Current (2 years 1 month)
    • Integrated and standardized financial data from SQL/ERP systems and loan databases into Databricks' Lakehouse platform, improving data accuracy and completeness by 25%, which enhanced forecasting and risk modeling reliability. • Automated key financial and risk KPIs (e.g., Gross Margin, Revenue Growth %, DTI, LTV) using SQL, Python, and Excel, reducing manual reporting time by 30% and enabling consistent performance tracking across finance dashboards. • Performed EDA on financial and borrower datasets using Python (pandas, matplotlib, seaborn) to identify revenue trends, anomalies, and credit risk drivers, directly informing FP&A strategy and improving credit risk segmentation. • Developed predictive models including ARIMA, Prophet, a
  • Massachusetts General Hospital
    Data Science Co-op
    Massachusetts General Hospital
    Feb 2024 - Jun 2024 (5 months)
    • Improved patient risk stratification by applying Latent Class Growth Analysis to EPDS survey data, outperforming traditional GMM by 8% accuracy in identifying depression trajectories. • Delivered 89% entropy (cluster separation), clearly distinguishing high-risk vs. low-risk groups for targeted interventions. • Built Bayesian Networks mapping relationships among risk factors, enabling clinicians to understand causal pathways. • Partnered with Harvard PhDs to ensure HIPAA-compliant workflows, balancing advanced modeling with strict healthcare privacy standards.
  • Indium
    Data Analyst
    Indium
    May 2020 - Jul 2022 (2 years 3 months)
    • Extracted, cleaned, and transformed multi-source client datasets (~50M+ records across sales, billing, and usage) using SQL, Python, and ETL pipelines, improving data reliability for downstream analytics and reporting. • Performed EDA and statistical modeling (correlation analysis, hypothesis testing) using Python (pandas, seaborn, scipy) to uncover e-commerce sales trends and telecom churn drivers, enabling clients to refine retention and growth strategies. • Designed and delivered 10+ interactive dashboards in Tableau, Power BI, and Excel to visualize KPIs such as revenue growth, conversion funnels, and customer churn, supporting executive reviews and client decision-making. • Collaborated with client Data Science, Marketing, and Su
Education verified_user 0% verified
  • Northeastern University
    Master of Science
    Northeastern University
  • Jaypee University of Information Technology
    Bachelor of Technology
    Jaypee University of Information Technology
Projects (professional or personal) verified_user 0% verified
  • G
    Generative AI Research Assistant
    • Developed a GenAI-powered RAG system using LangChain, OpenAI embeddings, and FAISS, with a Streamlit interface for URL ingestion, real-time parsing, and natural language querying—reducing manual research time by 85%. • Implemented prompt engineering and semantic search techniques to ensure responsible AI-aligned and reliable information retrieval, improving accuracy and trust in analyst decision-making. • Engineered an NLP-based book recommendation system using LLMs (OpenAI embeddings, Hugging Face models) and ChromaDB for semantic search, achieving 78% accuracy in zero-shot genre classification across 7,000+ titles with sentiment filtering via fine-tuned RoBERTa. • Built a scalable, real-time vector search pipeline using LangChain, C
  • A
    AI-Powered Book Recommendation Engine
  • C
    Credit Card Anomaly Detection