Yashpal Suwansia

WORK HISTORY

EDUCATION

ABOUT YASHPAL SUWANSIA

IIT Bombay Alum | Transforming 15+ Years of Advanced Mathematics into Scalable Machine Learning SolutionsData Scientist and Machine Learning professional focused on building data-driven solutions that solve real business problems. I specialize in predictive modeling, feature engineering, and end-to-end machine learning pipelines.My core expertise lies in tree-based algorithms such as Random Forest, XGBoost, and LightGBM, along with strong SQL-based analytics. I enjoy transforming complex datasets into actionable insights that drive better decisions.Technically, I work extensively with Python, SQL, Pandas, NumPy, and Scikit-learn for modeling, experimentation, and evaluation. I am particularly interested in customer analytics, conversion prediction, and model explainability.I am always exploring new ways to combine machine learning with practical business applications and scalable data solutions.Technical Toolkit:Languages & Core: Python (Pandas, Tensorflow, Scikit-Learn, Pytorch, Seaborn, NumPy, Matplotlib, Statsmodel), SQL.Machine Learning: Regression, Classification, Clustering, SVM, Naive Bayes, k-NN, Decision Trees, Ensemble Models (Random Forest, XGBoost, LightGBM), Neural Networks, Gradient Descent Variants (Adam, RMSProp), Hyperparameter Tuning, Cross-ValidationData Engineering: Feature Engineering, EDA, Cross-Validation, Regularization, Hyperparameter Tuning.Certifications: Google Advanced Data Analytics Professional Certificate & DeepLearning.AI Machine Learning Specialization.Ed-Tech Expertise: 6+ years contributing to data-driven content and platforms for competitive exams, gaining exposure to large-scale learner data and product-oriented thinking.I am passionate about applying ML to education—building adaptive learning systems and personalized recommendation engines—but I am equally keen to use my quantitative rigour to any high-impact data science role.Open to: Data Scientist, ML Engineer, or Quantitative Analyst roles (Remote/Full-time).