- 🔭 I’m currently working on data science and causal inference projects in industry and academia.
- 🌱 I’m learning Bayesian statistics, advanced causal methods, and large-scale predictive modeling.
- ⚡ Fun fact: I enjoy building interactive dashboards, automating analytics pipelines, and contributing to open-source projects.
- 🎯 Goal: Pursuing a PhD in Data Science or Statistics, focusing on causal inference, longitudinal modeling, and machine learning applications.
- Experimentation App — Recommendation engine integrating user behavior and trends, improving engagement.
- Explore Bangladesh — ML model predicting household vulnerability using socio-economic indicators.
- Dengue Forecasting Models — Comparative analysis of ML and statistical time-series models for outbreak prediction.
- StatVizPro Shiny App — Interactive visualization of probability distributions for educational and analytical purposes.
Statistical Methods: Causal Inference (PSM, IPTW, G-Methods), Longitudinal & Survival Analysis, Bayesian Modeling, GLMs, Time Series, Multivariate Statistics
Data Visualization: ggplot2, Seaborn, Matplotlib, Shiny, Looker Studio, Superset
Other Tools: GitHub Actions, Docker, Cloud Technologies, Experimental Design, Analytics Pipeline Automation
- ✉️ Email: sarkerbishal02@gmail.com
- 🔗 LinkedIn: linkedin.com/in/bishal-sarker
- 🐦 Twitter: @absbazz_43
