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Data Science with 2+ years in Data Analysis & Machine Learning
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Data Scientist with an M.Tech in IT and 2+ years of experience in data analysis, machine learning, and real-world dataset modeling. Skilled in Python, SQL, and building end-to-end ML solutions including time-series anomaly detection and predictive modeling. Experienced in feature engineering, EDA, and deploying models using Streamlit with strong focus on business impact. Proficient in ETL pipelines, data preprocessing, and handling large structured datasets. Combines domain knowledge with statistical and machine learning techniques to deliver actionable insights. Seeking entry-level roles in Data Science and Machine Learning Engineering.
Utkal University
M.Tech · IT
August 1, 2023 – June 30, 2025
OUTR
Bachelor's · Urban Planning
August 1, 2017 – June 30, 2021
EVOASTRA Ventures Pvt Ltd
2-Data scientist Intern
December 1, 2025 – March 1, 2026
India
Rudrabhishek Enterprises Private Limited
1-Data Analyst
December 1, 2023 – December 1, 2025
India
Agent-Performance-Analytics
June 1, 2026 – Present
Conducted end-to-end crime data analytics by cleaning, preprocessing, and integrating large-scale datasets using Python (Pandas, NumPy) to uncover trends and patterns in crime distribution. Developed interactive geospatial visualizations (crime heatmaps, hotspot analysis) to identify temporal and regional crime concentration, aiding strategic decision-making. Built a business-intelligence dashboard to report actionable insights, leveraging EDA and data engineering to support policy planning and crime prevention initiatives.
Customer Churn Prediction & Model Deployment
June 1, 2026 – Present
Developed an end-to-end churn prediction model using classification algorithms, performing data cleaning, feature engineering, and exploratory analysis to identify key drivers of customer churn. Evaluated model performance using metrics such as accuracy, precision, recall, and ROC-AUC, and optimized hyperparameters to improve predictive reliability. Deployed the trained model as a production-ready application with seamless input processing and real-time churn predictions for business decision-making.
Lloyds Banking Group Data Science Job Simulation on Forage
December 1, 2025 – December 1, 2025
Completed a customer churn prediction simulation for the Data Science & Analytics team at Lloyds Banking Group, building a Random Forest-based model achieving ROC-AUC of 0.82. Executed advanced preprocessing (missing value handling, categorical encoding, feature scaling) using Python libraries including pandas, scikit-learn, and matplotlib. Performed hyperparameter tuning with GridSearchCV and leveraged feature importance analysis to generate actionable business insights.
BCG Data Science Job Simulation on Forage
December 1, 2025 – December 1, 2025
Conducted a customer churn analysis simulation for XYZ Analytics, defining investigative strategy and identifying key client data drivers. Performed end-to-end analysis using Python (Pandas, NumPy) and visualization techniques; engineered and optimized a Random Forest model achieving 50% recall in churn prediction. Delivered an executive summary translating model outcomes into actionable business insights for data-driven decision-making.
Python Programming: Machine Learning, Deep Learning
Udemy
June 1, 2026 – Present
Professional Certificate of Agile and Scrum Business Analyst
Udemy
June 1, 2026 – Present
Microsoft Excel- Beginner to Advance with Example
Udemy
June 1, 2026 – Present
Business analysis
Udemy
June 1, 2026 – Present
AI & ML Made Easy: From Basic to Advanced
Udemy
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio, including simulations with Lloyds Banking Group and BCG, indicates an interest in applying data science to real-world business problems. The academic projects and certifications show a proactive approach to learning and skill development. The blend of data analysis and machine learning engineering skills, along with exposure to various industries (banking, consulting, urban planning, energy), suggests adaptability and a broad interest in data-driven solutions. The target role of Data Science aligns well with their demonstrated skills and project experience.
Soft Skills & Operational Fit
The candidate demonstrates a structured approach to problem-solving through their project descriptions, particularly in defining investigative strategies and translating technical outcomes into business insights. Their experience in collaborative team settings for the anomaly detection system suggests an ability to work effectively in a team. The certifications in Agile and Scrum Business Analyst indicate an understanding of agile methodologies, which is beneficial for operational fit.