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Conducted comprehensive risk assessments by identifying key business risks, evaluating internal controls and testing their design and operating effectiveness using a risk-based approach. Delivered actionable recommendations that reduced control gaps, enhanced compliance and improved overall process reliability.
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Creatives on Contra have earned over $150M and we are just getting started
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SUBTIQ AI – predictive analytics platform for behavioral risk detection
An AI-powered web application designed to identify behavioral risk patterns and support the early detection of substance-use tendencies using machine learning and data analysis.
Overview
As part of a multidisciplinary team, I contributed to the development of a predictive analytics system that analyzes behavioral and digital usage patterns to estimate potential risk indicators. The project involved building and evaluating multiple machine learning models and creating a functional web-based prediction system.
My contributions
*Data preprocessing and feature preparation
*Machine learning model evaluation
*Prediction pipeline implementation
*UI and web application development
*System testing and deployment support
Technologies used
Python, Pandas, Scikit-learn, CatBoost, Random Forest, Logistic Regression, Flask, SQL
Key outcomes
Developed a working end-to-end ML prediction pipeline
Evaluated multiple models, with CatBoost achieving approximately 99% accuracy
Built a functional web application for risk prediction
Created a structured workflow for data preprocessing, prediction, and performance evaluation
This project was presented at the 14th International Conference on Contemporary Engineering and Technology (ICCET 2026) and reflects my interest in applying AI and data-driven systems to real-world problem solving.
💡 The most dangerous sentence an Amazon seller can say: "I already checked that months ago."
Profit leaks don't happen once. They repeat every month. The reimbursement you claimed in January could be waiting again in July. The stranded unit you fixed last quarter could be replaced by two new ones.
That's why the audit habit isn't a one-time cleanup. It's a monthly discipline.
Here's the 5-point check I run for every client, every 30 days:
Reimbursement Report – unclaimed credits.
Stranded Inventory – unsellable stock.
FBA Fee Preview – dimension mismatches.
Return Reasons by SKU – fix the listing, cut returns.
Inventory Age Report – identify slow movers before they eat your margin.
Time required: 30–40 minutes. Tools: just your Seller Central login.
I've found anything from $200 to $2,000 doing this — on accounts that looked healthy from the dashboard. No new products. No additional ad spend. Just recovering what was already owed and stopping what was quietly draining.
The sellers who stick with this keep more of what they earn. It's that simple.
If you haven't run any of these reports in the last 30 days, today's a good day to start. Which one will you open first?
#AmazonFBA #ProfitRecovery #FBAAudit #EcommerceTips #AmazonSeller #BusinessHealth