Open to Data Science & ML Roles

Ali Murtaza

Data Scientist & Machine Learning Engineer building production-grade predictive pipelines and autonomous AI agent architectures. 10+ shipped projects spanning dual-model platforms, Explainable AI (SHAP), and asynchronous execution runtimes.

shap_values.explain(candidate_profile) → outcome: high impact
+ scikit-learn & python + copilot sdk agentics + 96.99% r² regression + shap interpretability + power bi dashboards + 99/100 intern eval
Ali Murtaza

Experience & Fellowships

Starting
Oct 2026
Selected Participant — Core Skills Cohort
McKinsey & Company — McKinsey Forward Program (Global)
  • Selected for a competitive global initiative focusing on structured business problem-solving, digital agility, and executive communication.
  • Applying data-backed decision frameworks to translate analytical models and machine learning outputs into strategic business strategy.
Business Problem SolvingDigital AgilityData Strategy
Jun 2026 —
Present
Technical Operations Facilitator
NOBEL Navigators (USA) — Remote
  • Facilitated technical enablement workflows for international cohorts across a global social-learning platform operating in 100+ countries.
  • Organized structured public speaking and technical communication tracks, standardizing collaborative problem-solving across distributed cross-functional teams.
Technical EnablementGoogle WorkspaceOperational Delivery
Mar 2026 —
May 2026
Data Science Intern
DevelopersHub Corporation — Faisalabad, Pakistan
  • Delivered 9 end-to-end machine learning pipelines across banking, retail, and healthcare datasets, earning a 99/100 performance evaluation score.
  • Engineered automated data preprocessing and validation scripts in Python (Pandas/NumPy), mitigating data leakage and cutting preprocessing time by 35%.
  • Constructed interactive Power BI dashboards linked to SQL queries, translating model classification outputs and predictive drivers into executive reporting.
PythonScikit-learnPandasPower BISQLSHAP

Featured Machine Learning & AI Systems

Financial Lead Scoring & SHAP 91% ROC-AUC

Benchmarked Random Forest against Logistic Regression classifiers for bank term deposits, applying SHAP values to explain feature contributions (call duration, account balance, age) to financial decision-makers.

Scikit-learnSHAP (Explainable AI)Random ForestLogistic Regression
Customer Segmentation Engine K-Means · PCA

Engineered an unsupervised customer clustering pipeline using PCA dimensionality reduction and K-Means to identify and visualize 5 actionable demographic and spending profiles.

K-MeansPCADimensionality ReductionMatplotlib
E-Commerce BI Intelligence Power BI Dashboard

Interactive business intelligence report analyzing transaction patterns, profit margins, and cohort performance designed for non-technical executive decision-making.

Power BIDAXData ModelingSQL
Bookstore Relational SQL Engine MySQL · 8 CTEs

Normalized relational schema with 500+ records demonstrating window functions, CTEs, running revenue totals, and complex joins for revenue trends and inventory audits.

MySQLWindow FunctionsCTEsRelational Design

Technical Skills

Languages & Core
PythonSQLC++JavaScript (ES6+)DSA (Python)
Machine Learning
Scikit-learnSHAP (Explainable AI)Random ForestLogistic RegressionGridSearchCVK-Means / PCA
AI & Agentics
GitHub Copilot SDKAutonomous AgentsAsyncIOStreamlit CloudPrompt Engineering
Data & BI
Pandas / NumPyPower BIMatplotlib / SeabornSQLite / MySQLGit / GitHub

Education & Credentials

Government College University Faisalabad
Bachelor of Science in Computer Science (BSCS)
2024 – PRESENT · 6TH SEMESTER · CGPA: 3.17 / 4.0

Core coursework: Data Structures & Algorithms, Object-Oriented Programming, Database Systems, Artificial Intelligence, and Software Engineering.

Resume

PDF
Ali Murtaza — 1-Page ATS Resume
Tailored for Data Science & Machine Learning Engineering Roles
06 · reach out

Let's build something
impactful together.

Actively interviewing for Junior Data Scientist and Machine Learning Engineering positions. Available for remote roles or on-site opportunities.