---
title: "Mohammed Luqmaan - Technical Apprentice in India | Tal"
description: "Meet Mohammed Luqmaan, Analytics and Engineering | Christ University | Building Real-World AI Solutions based in India. AI stack includes antigravity, claude code, and claude."
image: "https://tal.club/meet/mohammed-luqmaan/share-image"
---

# Mohammed Luqmaan on Tal

## Headline

Analytics and Engineering \| Christ University \| Building Real\-World AI Solutions

## About

I’m deeply interested in data science, analytics, and data\-driven problem solving, with a strong focus on building practical solutions using real\-world data\. As a Data Science Apprentice at Target and a student at CHRIST University, I’ve gained hands\-on experience across the data lifecycle, from data preprocessing and exploratory analysis to model development and evaluation\. My work and learning have involved: Designing and experimenting with machine learning and deep learning models Working with AI systems and large language models \(LLMs\) for applied use cases Applying statistical thinking and analytics to derive meaningful insights Translating business or problem statements into data\-driven approaches I enjoy working at the intersection of technology, analytics, and impact, and I’m particularly motivated by projects that emphasize practical implementation over theory alone\. Currently, I’m focused on strengthening my expertise in data science and AI, building scalable and responsible solutions, and continuously learning through hands\-on experimentation and real\-world challenges\.

## Location

India

## AI stack

antigravity

claude code

claude

codex

langchain

langgraph

## Work experience

Technical Apprentice at Target, Feb 2026 \- Aug 2026 · 7 mos, Bengaluru, Karnataka, India, Worked extensively with SQL and Google BigQuery to extract, transform, and validate business data across multiple datasets and schemas\. Supported Weekly Business Review \(WBR\) reporting by developing and optimizing SQL queries for key retail KPIs, including Sales, Demand, Units, Traffic, Returns, Cancellations, ASP, AOV, and UPO\. Analyzed retail business funnels such as Traffic, Items, Partners, Operations, and Guest metrics to understand business performance and support data\-driven decision\-making\. Built reusable SQL pipelines and prepared stakeholder\-ready query documentation while debugging schema dependencies and validating data quality\. Developed ML\-ready datasets by creating intermediate and aggregated tables, gaining exposure to enterprise data engineering workflows and feature engineering concepts\. Worked with the Target\+ Partner Performance system to understand vendor performance analytics, recommendation systems, Random Forest\-based prediction models, and business impact estimation\. Built an internal Custom GPT for Partner Scorecard Analysis, enabling users to upload partner performance files and receive automated analytical summaries and dashboard\-style insights\. Developed a Custom GPT for GCP SQL Query Assistance, allowing analysts to generate reusable SQL queries for commonly used datasets such as Sales, Demand, Item, and Calendar tables, improving productivity and reducing repetitive manual effort\.

Business Intelligence and AI Led Researcher at Streamoid CXO, Dec 2025 \- Jan 2026 · 2 mos, Bengaluru, Karnataka, India, Analyzed retail and fashion industry data to support pricing, promotions, and sales performance\. Worked on campaign analysis including selling price windows, discounts, and Buy\-1\-Get\-1 offers using ISO week–based timelines\. Performed trend and demand analysis to understand customer behavior and seasonal patterns\. Cleaned, structured, and validated datasets for reporting and insights\. Translated data findings into business\-friendly insights for cross\-functional teams\. Gained strong understanding of how the fashion retail ecosystem works across business, market, and technical perspectives\.

AI/ML Intern at Skill Vertex, Oct 2022 \- Jan 2023 · 4 mos, Bangalore, Worked on real\-world Machine Learning and Deep Learning projects for predictive and classification tasks\. Built a House Price Prediction model using Linear Regression, Random Forest, and Gradient Boosting\. Developed a CNN\-based image classifier \(cats vs dogs\), gaining hands\-on experience in computer vision and deep learning frameworks\. Performed data cleaning, feature engineering, and model evaluation using standard regression and classification metrics\. Implemented end\-to\-end ML workflows in Python, from preprocessing to model training and evaluation\.

## Education

Master of Science, Artificial Intelligence and Machine Learning, Christ University, Bangalore

Bachelor of Computer Application, St\. Francis College Bengaluru

[View the original profile](https://tal.club/meet/mohammed-luqmaan)

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