Thomas Preetham Nammi
Chicago,IL
Summary
Innovative and results-oriented Machine Learning Engineer with 5+ years of experience in designing, building, and deploying AI/ML solutions using Google Cloud Platform (GCP), Vertex AI, and modern MLOps practices. Proven expertise in developing scalable machine learning models, integrating APIs, and implementing CI/CD pipelines for automated deployment. Adept at working in cross-functional teams to deliver impactful, data-driven products across cloud-native environments.
Overview
7
7
years of professional experience
1
1
Certification
Work History
Senior Consultant
Sogeti by Capgemini
01.2024 - Current
- Built a text classification model using scikit-learn and TF-IDF to categorize customer support tickets into priority levels; improved response time by 35% and automated triage of 80% of incoming tickets.
- Developed an automated QA validation tool in Python + SQL to monitor ETL pipeline outputs against 15+ custom business rules, integrated into the CI/CD process, and reduced manual QA time by 40%.
- Data Platforms Quality Assurance Testing for various applications by executing over 10000 test cases across multiple projects, identifying and reporting critical defects, improving product quality, and reducing defect density by 48%.
Data Science Intern
Torqata
05.2023 - 09.2023
- Programmed and deployed a Data Alerting Pipeline on the Google Cloud Platform that generates alerts on the company’s data if found erroneous, with 100% efficacy. The GCP Vertex AI pipeline ensures data integrity, providing all applications with clean data to produce accurate results for client-facing products. This upholds the highest data quality standards and contributes to seamless user experiences.
- Spearheaded Econometric Analysis to statistically prove that our client’s gross margin returns on investment (GMROI) increased by 35%, thereby quantifying the value added by Torqata’s Inventory Optimization tool.
- Predicted a 20% increase in sales orders in the control stores in response to the positive behavior of the optimization tool.
Data Science Consultant
Mastercard
11.2021 - 07.2022
- Built a framework that uses Hadoop computing power, Machine Learning, and Automation to enable scalable delivery of the Advisory vertical products, minimizing 80% of manual efforts and time from roughly 200 hours to 40 hours.
- Churn Prediction (Classification & Regression): Analyzed credit card dataset of millions of customers, performed exploratory data analysis, and handled imbalance using SMOTE. Implemented XGBoost, Random Forest, Naïve Bayes, and Support Vector Machine classifiers to predict churn and obtained the best AUC score of 0.86 with Random Forest classifiers. Extended the analysis by predicting the attrition duration of potential churn candidates using Regression.
Business Technology Analyst
Deloitte USI
04.2018 - 04.2020
- Implemented the PESTEL Analysis, Porter’s Five Forces, Blue Ocean Strategy, and SWOT Analysis frameworks to map the e-commerce ecosystem and understand the client’s positioning in the market.
- Analyzed Sales Data and derived observations of unused potential to push higher sales, increasing them by 22%.
- Presented opportunities to improve the current discounting strategy & consequently increase the Return on Investment by 1.65 million dollars.
- Saved 15+ hours weekly on the delivery of Project Status, Attrition, and other relevant reports through extensive automation of spreadsheets, presentations, and visualizations.
- Reported red flags critical to a project’s performance by analyzing dashboards built on specific metrics & KPIs.
Education
Master of Science - Technical Entrepreneurship and Management (Concentration: Data Science)
University of Rochester
Rochester, New York12.2023
Post Graduate Diploma - Business Analytics (PGDBA)
ISI Kolkata, IIT Kharagpur, and IIM Calcutta
10.2021
Skills
- Certifications – Microsoft Certified Power BI Analyst; ISTQB Certified Foundation Level Tester
- Languages – Python Cloud – AWS, GCP & Azure DBMS – MySQL, Postgres Visualization – Power BI, Tableau, Qliksense
- Tools – GIT, Alteryx, MS Excel Libraries – NumPy, Pandas, Scikit-Learn, Seaborn, Matplotlib, Keras, PyTorch & Tensorflow
Accomplishments
Brain MRI Segmentation (Clustering): Implemented Rough Possibilistic Type 2 Gaussian Kernelized Fuzzy C Means Clustering on Brain MR Image Segmentation into its respective soft tissues with Bias Field Correction & Skull Stripping. Achieved an Accuracy of 97.86% on the Grey Matter of a T1-weighted MS Lesion brain MRI in the Z70 plane. Reduced the time of execution of the segmentation algorithm by 33.75% compared to the base model; presented at the IEEE ICCSP’18 conference and published a research paper on the same in the IEEE Xplore.
Certification
Microsoft Power BI Data Analyst
ISTQB Foundation Level Tester
Work Availability
monday
tuesday
wednesday
thursday
friday
saturday
sunday
morning
afternoon
evening
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Timeline
Senior Consultant
Sogeti by Capgemini
01.2024 - Current
Data Science Intern
Torqata
05.2023 - 09.2023
Data Science Consultant
Mastercard
11.2021 - 07.2022
Business Technology Analyst
Deloitte USI
04.2018 - 04.2020
Post Graduate Diploma - Business Analytics (PGDBA)
ISI Kolkata, IIT Kharagpur, and IIM Calcutta
Master of Science - Technical Entrepreneurship and Management (Concentration: Data Science)
University of Rochester
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