Data Science and Machine Learning professional with experience in Python, SQL, Predictive Analytics, Machine Learning, Deep Learning, Data Cleaning, Feature Engineering, and Model Development, complemented by industry ex…
Data Science and Machine Learning professional with experience in Python, SQL, Predictive Analytics, Machine Learning, Deep Learning, Data Cleaning, Feature Engineering, and Model Development, complemented by industry exposure at Accenture. Skilled in building end-to-end Machine Learning solutions including data collection, preprocessing, feature engineering, model selection, performance optimization, deployment, and validation using industry-standard methodologies. Hands-on experience developing predictive models using XGBoost, Random Forest, Decision Trees, Linear Regression, Logistic Regression, and Gradient Boosting, and other supervised learning algorithms. Built a customer churn prediction and Next Best Action solution at Accenture, using SHAP to explain customer-level churn drivers and convert model scores into targeted retention actions. Proficient in Python libraries including NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, with strong expertise in exploratory data analysis (EDA), data visualization, statistical analysis, and handling complex structured datasets. Experienced in SQL database management, model deployment and production support within an Agile delivery environment at Accenture. Developed a real estate price prediction model by scraping real-world datasets, performing extensive data preprocessing, and achieving 96–97% prediction accuracy using XGBoost, followed by cloud deployment on AWS. Certified in Data Science and Machine Learning through IIT Mandi (via Masai School) while successfully balancing full-time corporate responsibilities, demonstrating exceptional commitment to continuous learning and technical excellence. Recognized with the Accenture Excellence (ASE) Award for delivering outstanding client support, ownership, operational excellence, and consistently exceeding performance expectations.
<p>Worked on an end-to-end customer churn prediction solution using Python, SQL, Scikit-learn, and XGBoost on customer usage, billing, device, and service data.<br>
Performed feature engineering and model evaluation across Logistic Regression, Random Forest, and XGBoost using Precision, Recall, F1-score, and ROC-AUC.<br>
Generated churn probabilities and applied SHAP to identify key customer-level churn drivers.<br>
Worked on a rule-based Next Best Action (NBA) framework using churn risk, customer value, SHAP drivers, and eligibility rules for targeted retention actions.<br>
Wrote SQL to extract, join, and validate modelling datasets, running completeness and consistency checks before each refresh.<br>
Collaborated with business stakeholders and cross-functional teams during Agile sprint cycles to review model output, agree retention rules, and maintain solution documentation.<br>
Received the prestigious Accenture Excellence (ASE) Award for exceptional performance, ownership, and delivery excellence.<br>
Earned recognition from leadership for consistently delivering high-quality client support and maintaining strong stakeholder relationships.<br>
Identified as a high-performing employee and recommended by management for future career progression and promotion.<br>
Built strong client confidence through accurate delivery and proactive communication.</p>
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