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

    Built LLM-based data pipelines using RAG and transformer models for large-scale nonprofit datasets. Developed FastAPI microservices with GPT-based workflows, deployed ML systems on AWS, and improved semantic search using FAISS embeddings.

  2. Data Analyst I, Progment Software Technologies

    May 2021 — Dec 2023

    Built scalable ETL pipelines and real-time analytics with AWS and Airflow; automated dashboards in Power BI and Plotly Dash.

  3. ML Research Assistant, VIT

    Aug 2021 — Oct 2022

    Built image classification models using EfficientNet-V2; scaled training with Kafka and Delta Lake.

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