Data Scientist & ML Engineer | Building intelligent systems that turn data into insight | Skilled in Python, ML, Deep Learning, NLP, MLOps & deployment | Passionate about solving real-world problems with scalable, production-ready AI solutions
I’m a Data Scientist with a passion for transforming data into actionable intelligence.
My expertise lies in Machine Learning, Deep Learning, and Statistical Modeling, with hands-on experience in building end-to-end data pipelines, predictive models, and deployed AI applications.
I love working at the intersection of data, code, and business impact — whether it’s forecasting demand, detecting anomalies, or designing NLP models that understand human language.
- Data Science & Analytics: EDA, feature engineering, hypothesis testing, and visualization
- Machine Learning: Regression, classification, clustering, and model tuning
- Deep Learning: CNNs, LSTMs, Transformers (BERT, GPT)
- MLOps & Deployment: MLflow, Docker, FastAPI, Streamlit, and AWS
- Languages: Python, SQL, Bash
- Libraries: Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, XGBoost
- Visualization: Matplotlib, Seaborn, Plotly, Power BI
- Workflow: Git, Jupyter, Airflow, MLflow
- Cloud: AWS, GCP, Azure
- Building scalable ML pipelines and feature stores
- Improving model reproducibility with MLOps
- Exploring cutting-edge NLP techniques (LLMs, fine-tuning)
- Sharing knowledge through open-source projects and notebooks
- 📊 Exploratory Data Analysis (EDA) — real-world datasets & insights
- 🤖 Machine Learning Models — from regression to XGBoost & ensembles
- 🧠 Deep Learning Projects — NLP, computer vision, and time-series
- ☁️ Deployed Apps — Streamlit dashboards & FastAPI endpoints
- 🧩 Reusable Code Templates — data cleaning, pipelines, and utils
- 💼 LinkedIn:(https://linkedin.com/in/e8arpit)
- 🐦 Twitter: (https://twitter.com/e8arpit)