Software Engineer with 1+ years in Machine Learning, Generative AI, and Python.
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Software Engineer with hands-on expertise in Python, SQL, Machine Learning, and Generative AI. Proficient in designing predictive models, deep learning pipelines, and RAG-based intelligent systems. Experienced in ETL workflows, data visualization, and KPI reporting for production environments. Adept at leveraging LLMs, LangChain, FAISS/ChromaDB vector databases, and FastAPI to build scalable, data-driven applications that deliver measurable business impact.
GITA Autonomous College, BPUT
B.Tech · Computer Science and Engineering
August 1, 2019 – June 30, 2023
Nayagarh H.S. School
Higher Secondary · Science
June 1, 2017 – May 31, 2019
Saraswati Sishu Vidya Mandir
Secondary Education
June 1, 2008 – May 31, 2017
Pinnacle
Software Engineer
October 1, 2024 – Present
Bhubaneshwar, Odisha, India
Customer Revenue & Churn Analysis
June 19, 2026 – Present
Analyzed large-scale customer datasets to uncover churn drivers, revenue trends, and behavioral patterns influencing retention strategies. Validated and transformed raw data to ensure high-quality inputs for KPI computation and analytical reporting. Designed interactive Power BI dashboards visualizing retention metrics to support data-driven business strategy.
AI ChatPDF System
June 19, 2026 – Present
Architected an AI-powered document Q&A platform leveraging RAG pipelines for real-time semantic retrieval and context-aware responses from multi-page PDF corpora. Constructed document ingestion, embedding generation, and vector indexing workflows using FAISS, optimizing retrieval latency and response precision. Deployed scalable FastAPI REST backend and integrated an interactive Streamlit UI enabling seamless end-user document interaction.
View ProjectPrice Forecasting Analysis
June 19, 2026 – Present
Investigated historical pricing data to extract seasonality patterns and trend signals using statistical and time-series techniques. Forecasted future pricing behavior and surfaced insights through dashboards to inform strategic pricing decisions.
Customer Churn Prediction
June 19, 2026 – Present
Developed a Gradient Boosting classification model to forecast telecom customer churn, incorporating SMOTE to resolve class imbalance and improve recall on minority classes. Conducted thorough EDA and feature engineering to isolate high-impact churn indicators, boosting overall model interpretability. Shipped a production-ready Streamlit web application for real-time churn risk scoring accessible to non-technical stakeholders.
Object Detection System
June 19, 2026 – Present
Constructed a real-time deep learning object detection pipeline using YOLOv8 with custom tracking via Euclidean distance algorithms. Optimized model inference throughput for live video stream analytics, achieving low-latency detection suitable for edge deployment.
Lung Cancer Prediction System
June 19, 2026 – Present
Built a supervised ML model on clinical and behavioral datasets to predict lung cancer risk, applying feature engineering and cross-validation for robust performance. Evaluated outcomes using precision, recall, and F1 metrics; produced actionable insights to support early clinical detection.
Cultural Fit Analysis
The candidate's projects demonstrate a diverse range of applications, from financial analysis and customer churn prediction to AI-powered document Q&A and object detection. This breadth of interest and application suggests adaptability and a willingness to tackle varied technical challenges, which can be a good cultural fit for dynamic environments. The experience with SAP IS-U and ArcGIS also shows an ability to work with specialized domain tools. However, the experience is primarily in individual projects, and the single professional role is recent, limiting insight into long-term team collaboration or company culture alignment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving mindset and an ability to translate technical solutions into business value (e.g., improving billing accuracy, accelerating reporting cycles). The focus on deploying production-ready applications suggests an understanding of operational requirements. However, without direct assessment data, specific soft skills like teamwork, stress handling, or communication clarity in a collaborative setting cannot be fully evaluated.