Data Analyst with 3+ years in Big Data Analytics & Machine Learning
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Results-driven Data Analyst with a Master's in Big Data Analytics (GPA: 9.53) and 2+ years of hands-on experience turning complex data into actionable business insights. Proficient in SQL, Python, Power BI, and Azure Data Factory, with experience building end-to-end ETL pipelines, interactive dashboards, and predictive ML models. Experienced working with datasets of 100K–200K+ records across domains including sales, finance, HR, and operations. Seeking a Data Analyst role where I can drive data-driven decisions and deliver measurable business impact.
St. Xavier's College, Mumbai
Master of Science · Big Data Analytics
N/A – June 30, 2023
Thakur College of Science and Commerce, Mumbai
Bachelor of Science · Computer Science
N/A – June 30, 2021
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January 1, 2023 – April 1, 2023
Mumbai, Maharashtra, India
Loan Recovery Optimization & Predictive Analytics
June 24, 2026 – Present
Analysed 9,000+ loan accounts to identify key recovery drivers — found accounts with good payment history recover ~9x more than poor-history accounts. Built a segmentation framework classifying accounts by recovery potential to improve field team prioritisation and allocation strategy. Trained a logistic regression model (AUC: 0.69) and proposed data-driven channel strategies projecting an estimated +4–7% recovery improvement.
Mobile Sales Performance Dashboard
June 24, 2026 – Present
Designed an interactive Power BI dashboard analysing 160M+ in mobile sales across 5 brands, 10+ cities, and multiple payment methods. Developed 10+ DAX-based KPIs (Total Sales, Quantity, Transactions, Avg. Sales) with dynamic filtering by brand, city, month, and payment method. Identified weekend sales running 25–30% higher than weekdays; debit cards accounted for ~27% of all transactions — both used to inform promotional planning.
Employee Absenteeism Analysis
June 24, 2026 – Present
Analysed 740 employee attendance records across 21 features; applied IQR-based outlier removal to reduce variance in absentee hours by ~15%. Implemented and compared Random Forest and XGBoost classification models to identify absenteeism patterns and generate workforce productivity recommendations.
Azure Data Factory ETL Pipeline
June 24, 2026 – Present
Architected an end-to-end ETL pipeline using Azure Data Factory to process 5 Excel datasets from Azure Data Lake Storage (ADLS) to SQL Server using Bronze-Silver architecture. Implemented timestamp-based incremental loading with watermark tracking, reducing processed data volume by ~70% versus full loads. Developed reusable parameterised pipelines with ForEach, Lookup, Copy Data, and Stored Procedures, orchestrated via a master pipeline with parallel execution.
Cultural Fit Analysis
The candidate's project diversity, covering loan recovery, mobile sales, employee absenteeism, and ETL pipelines, indicates adaptability and a broad interest in applying data analytics across different business domains. Their experience in both internship and full-time roles, coupled with a Master's degree, shows a commitment to continuous learning and professional development. The explicit mention of soft skills and collaboration aligns well with a team-oriented culture.
Soft Skills & Operational Fit
The candidate demonstrates strong soft skills such as Stakeholder Communication, Requirements Gathering, Data Storytelling, and Cross-functional Collaboration, which are crucial for a senior Data Analyst role. Their project descriptions highlight collaboration with cross-functional teams and delivering insights to leadership, indicating good operational fit. The 'Outstanding Commitment' award also suggests a strong work ethic and reliability.