Open to opportunities

Anmol Deep

@anmoldeep_singh

Message

AI engineer building end-to-end ML pipelines; deploying FastAPI models with strong NLP and analytics.

India

Message

What I'm looking for

I’m looking for an entry-level AI/ML role where I can build end-to-end pipelines and deploy reliable models via production APIs (e.g., FastAPI), with strong emphasis on evaluation, monitoring, and practical business impact.

I’m an AI Engineer and BCA student at GNDU (Amritsar), specializing in Machine Learning and Data Science through the IIT Patna × Masai School program. I focus on the full AI/ML lifecycle—from data auditing and feature engineering to model evaluation, NLP, and production-ready API deployment.

In my D2C Churn Intelligence & Retention API project, I audited 7 datasets, built RFM segmentation, and improved ROC-AUC from 0.61 to 0.83, then shipped a Docker-ready FastAPI scoring service with Pydantic validation and testing. In my Credit Risk Classification System, I compared 4 classifiers and achieved 84.06% recall with AUC-ROC of 0.8623, cutting scoring time from 3–5 days to under 1 second per application while tracking experiments in MLflow with drift monitoring.

Experience

Work history, roles, and key accomplishments

Churn Retention API

IIT Patna × Masai School

May 2026 - Present (1 month)

Built a D2C churn prediction and customer retention system, auditing 7 raw datasets and generating 5 evidence-backed churn-risk hypotheses via EDA. Trained Logistic Regression vs tuned XGBoost (ROC-AUC 0.61 → 0.83) and deployed a Docker-ready FastAPI scoring service with Pydantic validation and batch prediction endpoints.

Python XGBoost LightGBM scikit learn Feature Engineering EDA fastAPI Pydantic Docker MLFlow

Credit Risk Classifier

IIT Patna × Masai School

Dec 2025 - Present (6 months)

Developed a credit risk classification pipeline by evaluating Logistic Regression, Decision Tree, Random Forest, and XGBoost on 1,000 loan applications, selecting a tuned Decision Tree (84.06% recall, AUC-ROC 0.8623). Reduced loan evaluation from 3–5 days to under 1 second per application while tracking experiments in MLflow and monitoring drift with PSI/KS-test and an automated retraining strateg

Python scikit learn XGBoost Decision Trees GridSearchCV MLFlow Model Evaluation PSI KS Test

Education

Degrees, certifications, and relevant coursework

Guru Nanak Dev University (GNDU)

Bachelor of Computer Applications (BCA), Computer Applications

2025 -

Pursuing a Bachelor of Computer Applications (BCA) with a focus aligned to AI/ML through related coursework and projects.

IIT Patna × Masai School

AI/ML Specialization (Online), Machine Learning & Data Science

2025 -

Activities and societies: Built D2C churn intelligence/retention APIs with FastAPI; audited 7 datasets (2,400 customers) and improved ROC-AUC from 0.61 to 0.83. Built a credit risk classification system comparing 4 models with tuned Decision Tree (84.06% recall, AUC-ROC 0.8623).

Completed an online AI/ML specialization in Machine Learning & Data Science covering supervised learning, feature engineering, model evaluation, NLP, and generative AI projects.