Data Scientist | 5 YOE | Predictive Modeling, Clustering | IIT BHU Grad

I’m a data science and analytics professional with over 5 years of hands-on experience delivering end-to-end machine learning and forecasting solutions across industries like logistics, healthcare, and aviation. A proud graduate of IIT BHU (2020), I specialize in building intelligent systems that transform raw data into strategic business insights.
At Jet2 Travel Technologies, I currently lead analytics initiatives focused on aviation operations. I designed and deployed a fuel uplift forecasting model across all airports on both monthly and weekly levels, achieving a 95% prediction accuracy. This has significantly optimized fuel planning and helped reduce excess fuel load — a direct impact on cost efficiency and environmental goals.

Prior to this, at XpressBees, I developed a delivery probability prediction model that scored an impressive 99.2% accuracy. This model has been instrumental in optimizing route planning, prioritizing high-risk shipments, and improving SLA adherence. Working with massive datasets (30M+ rows), I’ve built robust, scalable ML pipelines that integrate with real-time systems and deliver consistent performance under load.

? Technical Skills:

• Languages: Python (pandas, NumPy, scikit-learn, XGBoost, LightGBM), SQL
• ML/NLP: Predictive modeling, classification, time series forecasting, clustering, basic LLMs
• Visualization: Power BI, Tableau, Seaborn, Matplotlib

What sets me apart is my focus on real-world impact. I don’t just build models — I deliver business-ready solutions. From accurate forecasts to data-backed recommendations, I ensure that my work translates to measurable outcomes. My solutions are clean, interpretable, and tailored for decision-makers.
I’m passionate about collaborating with startups and enterprises alike, solving meaningful problems with data. Whether you're looking for a predictive model, a dashboard, or simply someone to make sense of your data, I can help.
Let’s connect and build something valuable together.