SANJAY SEKAR
Machine Learning EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Machine Learning Engineer with 3+ years in data engineering, machine learning & AI systems.
Data professional with 3+ years of experience in data engineering and machine learning, building scalable ETL pipelines, analytics platforms, and ML-ready datasets in enterprise environments. Proficient in Python, SQL, Informatica PowerCenter, AWS, and Tableau for developing data pipelines and analytics solutions. Hands-on experience in predictive modeling, anomaly detection, and LLM-powered Retrieval-Augmented Generation (RAG) systems using embeddings and FAISS vector databases. Recognized as Value Champion of the Quarter for delivering scalable, high-quality data solutions.
Bishop Heber College
Bachelor of Vocational · Information Technology
August 1, 2019 – June 30, 2022
Prodapt Solutions Pvt. Ltd.
Machine Learning Engineer | Data Scientist
September 1, 2022 – Present
Chennai, Tamil Nadu, India
Credit Risk Prediction System
January 1, 2024 – June 1, 2026
• Developed an end-to-end Credit Risk Prediction System to identify customers with a high probability of loan default using the Home Credit Default Risk dataset. • Designed and implemented a PostgreSQL-based data storage layer by loading and managing 11 financial datasets containing customer demographics, credit history, loan applications, and repayment information. • Built customer-level feature engineering pipelines by aggregating bureau records, previous loan applications, and repayment history into a single machine-learning-ready dataset. • Performed extensive data preprocessing, including missing value treatment, categorical variable encoding, feature selection, and data quality validation. • Trained and evaluated multiple machine learning models including Logistic Regression, Random Forest, and XGBoost to predict customer default probability. • Addressed class imbalance using class weighting techniques and evaluated model performance using ROC-AUC, Precision, Recall, F1-Score, and Accuracy metrics. • Developed a real-time prediction API using FastAPI, enabling risk assessment for individual customers through REST endpoints and Swagger UI. • Implemented model persistence, feature pipeline integration, and GitHub-based version control, along with comprehensive technical documentation and architecture design.
View ProjectAI-Powered KOL (Key Opinion Leader) Recommendation System | Generative AI Project
January 1, 2024 – June 1, 2026
• Developed an end-to-end AI-powered KOL Recommendation System to identify and recommend domain experts using semantic search and hybrid ranking techniques. • Collected and processed researcher data from OpenAlex API, built researcher profiles, and stored structured data in PostgreSQL. • Generated vector embeddings using Sentence Transformers (all-MiniLM-L6-v2) and implemented semantic similarity search using FAISS Vector Database. • Designed a hybrid ranking algorithm combining semantic similarity, citation count, and H-index scores to improve recommendation quality and researcher relevance. • Integrated Phi3 Mini LLM through Ollama to generate AI-powered explanations for researcher recommendations. • Built REST APIs using FastAPI and developed an interactive Streamlit dashboard for real-time researcher discovery and recommendation visualization.
View ProjectPython Essential Training
Udemy
January 1, 2025 – Present
Python for Data Science and Machine Learning Bootcamp
Udemy
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's experience spans traditional machine learning, data engineering, and cutting-edge generative AI projects, demonstrating adaptability and a willingness to learn new technologies. The diversity of projects (credit risk, KOL recommendation, RAG chatbot) indicates a broad interest in applying ML/AI to different domains, which aligns well with dynamic, innovation-driven environments. The focus on end-to-end solutions and collaboration suggests a team-oriented mindset.
Soft Skills & Operational Fit
The candidate's resume highlights collaboration with data engineers, analysts, and stakeholders, indicating good teamwork and communication skills. The 'Value Champion of the Quarter' award suggests a strong work ethic and ability to deliver high-quality solutions. The project descriptions show a structured approach to problem-solving and attention to detail in system design and documentation.