Data Scientist Building Value from Complex Data

I transform raw data into actionable insights using Python, SQL, and Machine Learning. My disciplined, analytical approach honed through rigorous UPSC preparation allows me to solve complex problems and drive business impact.

Featured Projects

A selection of projects that demonstrate my skills in action.

Retail Sales & Revenue Optimization

Conducted end-to-end EDA to uncover key business trends. Cleaned over 135k missing values, validated the Pareto Principle to find top revenue drivers, and mapped seasonal sales peaks to guide inventory and marketing strategy.

Python (Pandas, Matplotlib) Data Cleaning EDA Business Acumen
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Customer Segmentation using RFM & K-Means

Leveraged unsupervised learning to segment a customer base for targeted marketing. Built an RFM model, managed data skewness using Log Transformation, and identified 5 distinct customer segments (e.g., Champions, At Risk) to tailor marketing strategies.

Python (Pandas, Scikit-learn) Statistical Transformation K-Means Clustering Feature Engineering (RFM)
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Kindle Book Recommendation System

SVD & Collaborative Filtering: Solved the Sparsity Problem and built a Matrix Factorization model SVD tuned with 100 latent factors, achieving the lowest RMSE 3.4965 to generate highly personalized book recommendations.

Python (Suprise, Scikit - learn) SVD (Matrix Factorization) Collaborative Filtering Hyperparameter Tuning
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Kaggle: Handwritten Digit Recognizer

Designed and trained a sequential CNN with two convolutional blocks to automatically learn and extract hierarchical features (edges, corners, shapes) directly from pixel data. This model, regularized with Dropout, achieved a classification accuracy of 98.92% on the Kaggle test set to build a robust classifier for handwritten digits.

Computer Vision Python TensorFlow Scikit-learn

Publications & Articles

A collection of my technical writing and deep dives.

High-Accuracy Recommendation Engine

Built a high-performance recommendation engine using Singular Value Decomposition (SVD) to solve the "discovery fatigue" problem for a large book dataset.

Python Matrix Factorization SVD
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Professional Experience

Associate - British Airways

WNS Global Services

Dec 2019 – Dec 2021

  • Enhanced operational efficiency for the Workforce Management (WFM) team by performing critical data cleanup, manipulation, and transformation on large internal datasets.

Data Science Intern

The Sparks Foundation, Mentorness, Prodigy InfoTech, Cognorise InfoTech

Mar 2024 – Jun 2024

  • Improved dataset accuracy by 25% through a targeted data cleansing initiative, enabling more reliable analysis.
  • Developed interactive dashboards in Power BI and Tableau to present key findings to technical and non-technical stakeholders.
  • Applied various Scikit-Learn models for predictive analysis tasks across multiple internship projects.

Education

Master of Science, Computer Science

(Specialization: Data Science)

Mumbai University

Graduated 2021

Bachelor of Science, Computer Science

 

K.M. Agrawal College

Graduated 2018

Certifications & Training

  • Specialization in Data Science (ML & AI)

    AlmaBetter (Ongoing)

  • Introduction to Data Science

    CISCO

  • Data Analysis Essentials

    CISCO

  • Python (Basic to Advanced)

    Udemy

  • Python 3 Certification

    Programming Hub

A professional headshot of Allan C. Alex

About Me

I'm a Data Scientist based in Mumbai, India, with a Master's in Computer Science and a passion for uncovering the stories hidden within data. My journey into this field was driven by a deep curiosity and the analytical rigor I developed while preparing for the UPSC civil services exams a background that taught me discipline, deep research, and structured problem solving.

I thrive on the end-to-end data science process, from digging into messy datasets with SQL and Python to building predictive models and visualizing results with Tableau and Power BI. I'm always eager to connect with fellow professionals and explore new challenges.

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