Headline

Data Scientist | ML • Time Series • Statistical Modelling | Open to Opportunities

About

I build things with data, models that forecast commodity prices for government markets, severity models that help price insurance risk, and dashboards that turn raw match data into actionable sports insights. My background is statistics-first. MSc in Statistics from CHRIST University, two government internships, and a teaching role that forced me to explain complex methods clearly. That combination, rigorous foundations, real-world delivery, and the ability to communicate findings, is what I bring to a team. I'm looking for a data science role where I can contribute end-to-end, grow technically, and work on problems with real-world impact, whether that's at a high-growth startup or an established organisation. What I work with: Python · R · SQL · Scikit-learn · XGBoost · SARIMA · Tableau · Power BI · GitHub · MySQL 📩 nidhinjoseph1331@gmail.com

Location

Bengaluru

Work experience

Teaching Associate at Christ University, Bangalore, Sep 2025 - May 2026 · 9 mos, Bengaluru, Karnataka, India, Delivered statistics coursework to undergraduate and postgraduate students. Built evaluation frameworks to track performance trends and identify at-risk students early, essentially running a small data pipeline on academic outcomes. Teaching sharpened something most data roles reward: the ability to make complex analysis legible to a non-technical audience.

Data Science Intern at Government of Kerala (കേരള സർക്കാർ), Jan 2025 - Apr 2025 · 4 mos, Thiruvananthapuram, Kerala, India, Directorate of Economics & Statistics (Confidential Project) Built SARIMA-based forecasting models to predict commodity price movements across agricultural markets, work that fed directly into government economic planning. Handled messy, real-world data with missing values and seasonal irregularities. Delivered under NDA, which means the pressure to get it right was real.

Irrigation Design & Research Board Intern at Government of Kerala, May 2024 - Jun 2024 · 2 mos, Thiruvananthapuram, Kerala, India, Cleaned and engineered a multi-year government dataset, then trained a Random Forest Regressor that improved model efficiency by 30%. Used RandomizedSearchCV for hyperparameter tuning. The dataset had no clean documentation, figuring out what the data actually meant before modelling it was half the job.

Education

Master of Science - MS, Statistics, Christ University, Bangalore

Bachelor's degree, Statistics, University of Kerala