Open to new opportunities

Sahid
Ahmed

$

Tourism grad turned startup co-founder turned data scientist. I built the pricing engine at Rydz Mobility — a ride-booking startup I co-founded — then applied ML to credit default risk across 4,526 companies (92% recall) and churn prediction on 11,260 customers (88% recall, AUC 0.915). Currently finishing an MSc in Data Science at Deakin University.

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Sahid Ahmed
Sahid Ahmed
Data Analyst · Data Scientist
Available
top_model.py
92% recall · Credit Default
stack
Python · SQL · Azure AI
location
Gurugram, India
// skills

What I work with

A toolkit built through real projects across analytics, ML, and AI.

🐍
Core Languages
Primary stack for all data work — analysis, modelling, automation.
Python SQL Pandas NumPy
🤖
Machine Learning
From classical algorithms to ensemble methods and deep learning.
Scikit-learn SVM Random Forest K-Means SMOTE
0
% best recall achieved
☁️
Cloud & AI
Azure AI Computer Vision NLP / CLU Deep Learning
📊
Visualisation & BI
Turning data into decisions stakeholders can act on.
Tableau Power BI Streamlit Seaborn
📐
Statistics
Hypothesis Testing A/B Testing VIF
// experience

Where I've worked

Rydz Mobility
Analytics & Pricing Lead · Co-Founder
Jan 2026 – Present
  • Designed data-driven pricing models using demand elasticity analysis across airport, corporate, and outstation segments.
  • Built automated Tableau dashboards tracking KPIs in real time — reducing manual reporting effort significantly.
  • Translated EDA findings into pricing adjustments adopted directly by commercial leadership.
Marvel Corporate Services
Sales Analytics Associate
Aug 2016 – Aug 2020
  • Analysed 300+ monthly cases — root cause work that improved first-time resolution by 20%.
  • Automated Excel reporting workflows, reducing manual effort by 40%.
  • Tracked SLA compliance across enterprise accounts, proactively surfacing escalation risks.
// projects

Selected Work

End-to-end ML, risk, and AI projects built with real data.

01
MLRisk
Financial Default Prediction
92% recall on 4,526 companies using Logistic Regression with VIF feature selection and SMOTE. NSE equity risk-return analysis.
Python · Scikit-learn · SMOTE GitHub
02
MLRisk
Customer Churn Prediction
Segmented 11,260 customers with K-Means. SVM classifier at 88% recall, ROC-AUC 0.915. Retention strategy → 15–20% projected reduction.
Python · K-Means · Tableau GitHub
03
NLPAzure
Travel Booking CLU Bot
Conversational AI with 3 intents and 3 entities built in Azure Language Studio. Evaluated failure modes and edge cases across varied utterances.
Azure CLU · Python GitHub
04
CVAzure
Object Detection Pipeline
Azure Computer Vision API pipeline — bounding boxes, confidence scoring, structured CSV/JSON export. Robustness evaluation across occlusion and low-contrast scenes.
Python · Azure CV · Pillow GitHub
05
VizRisk
Insurance Claims Dashboard
$11M+ in claims analysed across vehicle type, demographics, and exposure. 6 strategic recommendations on premium recalibration.
Tableau · KPI Design Tableau
06
SQL
E-Commerce BI via SQL
10 business questions answered with complex multi-table SQL — segmentation, inventory, logistics, market basket. $2.5M+ in high-concentration inventory identified.
SQL · Multi-table Joins GitHub
View all projects

Let's build
something.

Open to data analyst, data scientist, and decision scientist roles. Also happy to connect on collaborations and freelance projects.

ahmedsahid11@outlook.com
LinkedInlinkedin.com/in/isahid11
GitHubgithub.com/isahid11
Portfoliosahidahmedportfolio.netlify.app
Mediummedium.com/@isahid11