I'm a Data Scientist with 3+ years of experience designing and deploying end-to-end machine learning systems for customer behavioral modeling, personalization, and predictive analytics. I specialize in feature engineering on large-scale transactional and behavioral datasets, model interpretability (SHAP), and translating predictive outputs into actionable business decisions. I'm proficient in Python, XGBoost, LSTM, AWS SageMaker, GCP Vertex AI, and MLOps workflows. I'm a strong communicator with a proven track record of cross-functional stakeholder collaboration and decision-support reporting.…

Muhammad Jawad Mufti

I'm a Data Scientist with 3+ years of experience designing and deploying end-to-end machine learning systems for customer behavioral modeling, personalization, and predictive analytics. I specialize in feature engineering on large-scale transactional and behavioral datasets, model interpretability (SHAP), and translating predictive outputs into actionable business decisions. I'm proficient in Python, XGBoost, LSTM, AWS SageMaker, GCP Vertex AI, and MLOps workflows. I'm a strong communicator with a proven track record of cross-functional stakeholder collaboration and decision-support reporting.…

Available to hire

I’m a Data Scientist with 3+ years of experience designing and deploying end-to-end machine learning systems for customer behavioral modeling, personalization, and predictive analytics. I specialize in feature engineering on large-scale transactional and behavioral datasets, model interpretability (SHAP), and translating predictive outputs into actionable business decisions.

I’m proficient in Python, XGBoost, LSTM, AWS SageMaker, GCP Vertex AI, and MLOps workflows. I’m a strong communicator with a proven track record of cross-functional stakeholder collaboration and decision-support reporting.

See more

Language

English
Fluent

Work Experience

Machine Learning Engineer at Elevvo Pathways
September 1, 2025 - October 1, 2025
Architected and deployed a production-grade multimodal deep learning system integrating computer vision and audio models for real-time user engagement monitoring, achieving a 40% improvement in inference speed on edge devices. Engineered an end-to-end model optimization and deployment pipeline using TensorFlow Lite and ONNX, reducing model latency and memory footprint by 35% while maintaining production-grade accuracy. Conducted deep EDA to surface behavioral patterns, validate data quality, and enrich feature representations, improving downstream model performance and interpretability. Designed and executed rigorous evaluation and benchmarking workflows to ensure reliability across heterogeneous edge device environments.
Data Scientist at Teknotize
March 1, 2024 - March 1, 2026
Delivered end-to-end data science workflows across customer analytics, personalization, and predictive modeling, including ETL design, data cleaning, feature engineering, model evaluation, and insightful reporting on large-scale e-commerce datasets. Built purchase propensity and repeat-buyer models by engineering behavioral, transactional, and engagement-based features from browsing, cart, and order activity logs. Trained, optimized, and evaluated models including XGBoost and LSTM, achieving strong accuracy and precision-recall, enabling early identification of at-risk customers for retention campaigns. Performed advanced EDA, customer segmentation, and SHAP-based interpretability analyses to uncover key shopping patterns and drivers. Translated model outputs into actionable retention and merchandising recommendations for cross-functional teams.
Machine Learning Engineer at ALIMCOSOFT (SMC-PRIVATE) LIMITED
February 1, 2023 - December 31, 2023
Designed and maintained ETL pipelines for structured customer behavioral and transactional data, supporting robust feature engineering and model training workflows. Built and optimized classification models for customer behavior prediction, improving precision-recall trade-offs and guiding business operation prioritization. Conducted EDA, risk segmentation, and hypothesis testing to surface behavioral patterns and performance drivers. Performed feature importance analysis and SHAP-based interpretability assessments to improve robustness and communicate findings to non-technical stakeholders. Collaborated with business and technical teams to translate model outputs into decision-support dashboards and actionable insights for planning and operations.

Education

M.S. in Computer Science at King Fahd University of Petroleum and Minerals (KFUPM)
January 1, 2024 - May 10, 2026
B.S. in Software Engineering at University of Lahore
February 1, 2019 - February 28, 2023

Qualifications

Add your qualifications or awards here.

Industry Experience

Software & Internet, Professional Services
    Customer Behavioral Modeling & Retention Decision Support System

    An end-to-end customer churn prediction and retention decision-support system designed for non-contractual service environments where churn is inferred from customer inactivity and behavioral patterns.

    Project Details:
    Developed a temporal behavioral modeling pipeline using customer activity, booking history, transactional behavior, engagement signals, and recency-frequency-monetary features.

    Engineered rolling-window features to capture customer behavior over time and support early churn-risk identification in a non-contractual business setting.

    Trained and evaluated machine learning and deep learning models, including XGBoost and LSTM, for customer churn prediction, retention modeling, and risk classification.

    Applied SHAP-based model interpretability to identify key churn drivers and explain model predictions to non-technical stakeholders.

    Designed a decision-support layer that translated churn-risk predictions into actionable retention recommendations for targeted customer intervention.