About Me

I'm a Data Scientist fluent in the language of messy data. I transform unstructured data into intelligent, scalable solutions that support automated decision-making across industries such as healthcare and finance.

With hands-on experience in LLMs, NLP, Apache Spark, Airflow, and cloud technologies like AWS, I specialize in building end-to-end pipelines and interactive dashboards that deliver real business impact.

🧠 CharanBot

Ask me anything about Sree Charan’s projects, skills, or experience!

Resume

Education

  1. University of Maryland, Baltimore County

    2024 — Present

    MS in Data Science (GPA: 3.822/4)

  2. Vellore Institute of Technology

    B.E. in Computer Science (CGPA: 8.46/10)

Experience

  1. Machine Learning Engineer, WikiCharities

    Aug 2025 — Present

    Architected LLM-driven data pipelines using RAG and transformer models for nonprofit datasets across 190+ countries. Built FastAPI-based microservices integrating GPT models for automated financial insights and reporting. Deployed scalable ML infrastructure on AWS (SageMaker, Lambda, S3) and improved semantic search using FAISS and embeddings, increasing metadata accuracy by 42% and reducing manual effort significantly.

  2. Data Scientist, Progment Software Technologies

    Apr 2021 — Nov 2023

    Designed end-to-end ML pipelines using LSTM and XGBoost for financial forecasting, improving prediction accuracy by 24%. Built large-scale NLP pipelines using BERT and Hugging Face to process 12K+ financial records daily. Developed anomaly detection systems (Isolation Forest, Autoencoders) and deployed scalable ML solutions on AWS SageMaker, improving performance, scalability, and model reliability.

  3. Data Analyst, Progment Software Technologies

    Feb 2020 — Mar 2021

    Performed exploratory data analysis on financial datasets, built SQL-based pipelines and dashboards, and supported clustering and anomaly detection models to improve reporting efficiency and early fraud detection.

Skills

  • Python
  • SQL
  • Spark
  • Airflow
  • TensorFlow
  • PyTorch
  • Transformers
  • LLMs
  • BERT, ClinicalBERT, BART
  • Apache Kafka
  • AWS (Lambda, S3, Glue, Redshift)
  • Databricks
  • Docker
  • Flask & Django
  • Power BI
  • Plotly Dash
  • MongoDB
  • MySQL
  • LangChain
  • Java
  • C++
  • Bash
  • Machine Learning
  • Deep Learning
  • NLP
  • RAG
  • Information Retrieval
  • Time-Series
  • Scikit-learn
  • XGBoost
  • Hugging Face
  • AWS (SageMaker, EC2)
  • CI/CD
  • FAISS
  • Pandas
  • NumPy
  • Tableau
  • Matplotlib
  • Seaborn
  • FastAPI
  • PostgreSQL
  • Redis

Portfolio

AI-Powered Medical Assistant using NLP & Transformers

Built a real-time healthcare assistant using ClinicalBERT and BART. Deployed via Flask, enabling symptom triage with 72% accuracy and 1.2s latency.

Skills: NLP, ClinicalBERT, Hugging Face, Flask

GitHub |

Customer Segmentation with Apache Spark

Segmented 250K+ customers using PySpark RFM + K-Means clustering. Improved processing speed by 40% and cluster clarity by 22%.

Skills: PySpark, MLlib, Clustering

GitHub

Facial Diagnosis with Deep Transfer Learning

Web app to detect health indicators from facial images. Achieved 85% accuracy with transfer learning on medical image datasets.

Skills: CNNs, Flask, Computer Vision

GitHub

Energy Consumption Forecasting

Forecasted building energy usage using XGBoost & LightGBM. Integrated weather APIs, optimized models with GridSearchCV.

Skills: Time Series, XGBoost, Hyperparameter Tuning

GitHub

Smart Floor Cleaning Robot (Raspberry Pi)

Designed a SLAM-enabled robot using Pi + Python for real-time obstacle detection and efficient cleaning.

Skills: Raspberry Pi, SLAM, Arduino

Show Demo