Data Analyst with 1+ years in data analytics, machine learning, and business intelligence.
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Master of Business Analytics graduate from UTS with expertise in data analytics, machine learning, and business intelligence. Skilled in analysing complex datasets, developing predictive models, and delivering actionable insights to support strategic decision-making and business improvement across healthcare, finance, marketing, and operational domains. Experienced in translating business requirements into practical, data-driven solutions that improve processes and support informed decision-making.
University of Technology Sydney
Master · Business Analytics
August 1, 2024 – June 30, 2026
B V Raju Institute of Technology
Bachelor · Computer Science and Business Systems
August 1, 2020 – June 30, 2024
Astron Energy
Operations Manager
January 1, 2026 – Present
Sydney, New South Wales, Australia
United Petroleum Pty Ltd
Operations Assistant
May 1, 2025 – January 1, 2026
Sydney, New South Wales, Australia
Optum (UnitedHealth Group)
Business Analyst Intern
December 1, 2023 – March 1, 2024
India
AI-Powered Hybrid Product Recommendation System
January 1, 2025 – Present
Designed and implemented a 7-step recommendation pipeline using TF-IDF, VADER sentiment analysis, FAISS vector search, and RAG-enabled LLMs. Integrated five recommendation signals through a weighted hybrid scoring framework to enhance recommendation quality. Evaluated recommendation performance using Precision@5, Recall@5, and NDCG@5 metrics to measure ranking accuracy and recommendation quality.
Telecom Marketing Campaign Analysis
January 1, 2025 – Present
Developed Logistic Regression and Random Forest models on 41,180 customer records to predict subscription outcomes, achieving 90% accuracy and an AUC of 0.80. Addressed class imbalance and engineered features from customer contact history to improve model performance. Delivered data-driven targeting recommendations to support marketing campaign optimization and improve ROI.
Diabetes Prediction using Clinical Indicators
January 1, 2025 – Present
Analysed 97,297 patient records to develop predictive models for diabetes risk assessment. Compared the performance of four machine learning algorithms using industry-standard evaluation metrics. Achieved the highest performance with LightGBM, delivering an AUC-ROC of 94.55% and 100% precision.
Loan Approval Prediction
January 1, 2025 – Present
Developed predictive models including Logistic Regression, Random Forest, and LightGBM on a 4,269-record financial dataset. Performed exploratory data analysis, feature engineering, and model evaluation to identify key loan approval factors. Conducted stakeholder analysis and defined project success criteria aligned with business objectives.
Breast Cancer Survival Estimation Using Machine Learning
January 1, 2024 – December 31, 2024
Developed an end-to-end machine learning solution to predict breast cancer survival outcomes using clinical and patient data, supporting data-driven healthcare decision-making. Performed data preprocessing, exploratory data analysis (EDA), feature engineering, dimensionality reduction (PCA), and model training to improve predictive performance and identify key survival indicators. Designed and documented the complete machine learning workflow using UML diagrams and structured development methodologies, covering data acquisition, model development, evaluation, and deployment planning.
Cultural Fit Analysis
The candidate's academic projects demonstrate a proactive approach to learning and applying data analysis techniques. However, the professional experience is heavily skewed towards operational management rather than direct data analysis roles, which might indicate a gap in practical, industry-specific data analyst experience. The transition from operations to data analysis suggests adaptability and a desire for career growth in analytics.
Soft Skills & Operational Fit
The candidate's experience as an Operations Manager and Assistant suggests strong organizational, team coordination, and problem-solving skills. The resume also highlights stakeholder engagement, communication, and critical thinking as core capabilities, which are valuable for a Data Analyst role requiring interaction with business users.