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Abdullah Ahmad

@abdullahahmad

Data Science Analyst at American Express

Gurugram, India

linkedin.com/in/abdullahjamilahmad/

American ExpressIndian Institute of Technology, Guwahati

Abdullah Jamil Ahmad is a Data Science Analyst with experience at American Express, where he has driven significant revenue growth by rebuilding profitability metrics and optimizing investment strategies. He has a strong background in machine learning, utilizing techniques like XGBoost and Random Forest for segmentation and prediction. He is proficient in Python and various data science tools, demonstrated through academic projects like Credit Risk Modelling.

Experience

Analyst: Data Science

American Express

•Jun 2022 - Present•Gurugram, India

Rebuilt a profitability metric subject to enterprise-level overhauls to quantify the projected revenues from Personal Loans and Income Capture Treatment for offer targeting and investment optimization that drives the incremental revenue of more than $308 million while collaborating with a team of more than 10 stakeholders. Launched the enhanced model while assuring the quality of variables adhering to strict governance standards. Analysed and refined the segmentation-based targeting logic for 10+ spend stimulating offers across 4 industries for 30+ Cards driving an ROI of up to 300% and raising the internal standards of 2 offers from Tier-3 to Tier-2. Implemented XGboost-guided segmentation rule generation to fine-tune the strategy and conducted hypothesis testing to read the significance of the results of the campaign performance. Received a Director-level recognition within 3 months of joining and three VP-level recognitions, one within 6 months, another within 9 months and another within 15 months of joining.

Education

Indian Institute of Technology, Guwahati

B.Tech

Jan 2018 - Present•Grade: 8.86

CBSE

Senior Secondary

Jan 2018 - Jan 2018•Grade: 92%

CBSE

Secondary

Jan 2016 - Jan 2016•Grade: 9.40/10

Skills

Python
C++
Pandas
Numpy
Seaborn
Scikit Learn
NLTK
Tensorflow
MS Excel
MySQL