Data Science with 2+ years in Python & Machine Learning
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Data Scientist and AI Engineer with 2.5 years of experience in Python, SQL, Machine Learning, Forecasting, and Generative AI solutions. Hands-on experience building AI-powered support systems, RAG pipelines, GPT-4 based assistants, forecasting models, and analytics workflows using LangChain, ChromaDB, FastAPI, and vector databases. Skilled in prompt engineering, embeddings, feature engineering, document-aware retrieval systems, and translating business problems into scalable AI-driven solutions.
Acharya Nagarjuna University
Bachelor's in Data Science · Data Science
August 1, 2020 – June 30, 2023
Sri Sai Ram Jr College
M.P.C
June 1, 2018 – May 31, 2020
SSC
SSC
June 1, 2014 – May 31, 2018
Trexedia Travel Technologies
Software Developer (Data Scientist / AI Engineer)
February 1, 2024 – Present
Bengaluru, Karnataka, India
Corporate Travel Demand Forecasting & Predictive Analytics
June 24, 2026 – Present
Built a Machine Learning and time-series forecasting pipeline using SQL, MySQL, and Python to predict travel demand, service utilization, and cancellation trends across travel operations. Performed EDA, preprocessing, and feature engineering using variables such as booking lead time, seasonality, service frequency, cancellation history, and monthly demand signals. Applied Facebook Prophet for forecasting and compared Linear Regression, Random Forest, and XGBoost models to estimate demand and cancellation likelihood. Evaluated performance using RMSE, MAE, and trend validation, delivering predictive insights to improve planning, service readiness, and operational decisions.
Trexedia Support Bot – AI-Powered Travel Support Chatbot
June 24, 2026 – Present
Developed an AI-powered support chatbot for Trexedia's travel booking platform to answer user queries related to bookings, tickets, timings, locations, travel policies, and platform services. Analyzed 80K+ booking, support, and operational records using SQL, Python, Pandas, and NumPy, and worked with complex unstructured and semi-structured travel support data. Implemented document-aware RAG pipelines using embeddings, LangChain, vector search, and prompt engineering to improve retrieval accuracy, reduce hallucinations, and deliver context-aware responses across structured and unstructured travel documents. Improved support efficiency by automating repetitive queries and reducing manual support/reporting effort by ~60%
Travel Operations Analytics & ML Data Intelligence Pipeline
June 24, 2026 – Present
Built a SQL and Python-based analytics pipeline to transform raw travel booking, inventory, support, and fulfillment data into clean, structured, ML-ready datasets. Processed and analyzed travel operations data across flights, hotels, transport, invoicing, cancellations, and support workflows to uncover service demand patterns and operational trends. Worked with complex multi-source travel datasets and performed data preprocessing, including null handling, duplicate removal, data transformation, and feature creation for downstream analytics and ML use cases. Created feature-ready datasets and reporting tables to support forecasting, support analytics, customer behavior analysis, and business dashboards. Improved data accessibility and reduced manual data preparation effort by ~30% through automated preprocessing and structured data transformation. Strengthened end-to-end understanding of the pipeline from transactional travel data → SQL extraction → Python preprocessing → analytics / ML consumption.
Java Full Stack course
Jspiders
June 1, 2026 – Present
Foundational Artificial Intelligence course aligned with SSC NASSCOM
SSC NASSCOM
June 1, 2026 – Present
Data Science Course Certification with high distinction
EXCELR
May 1, 2024 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong alignment with the target role of Data Science, particularly in the application of AI and ML to real-world business problems within the travel domain. The breadth of skills across data analysis, machine learning, and generative AI, combined with experience in full-stack development (Java certification), suggests adaptability and a willingness to learn diverse technologies. The focus on practical, impactful solutions aligns well with a results-driven culture.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a focus on improving operational efficiency and delivering data-backed decisions, suggesting a results-oriented approach. Collaboration with product and operations teams is also mentioned, indicating a team-oriented mindset. The ability to translate business problems into AI-driven solutions points to strong problem-solving and analytical skills.