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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
Axience
Business Development Associate (Data Analysis & Reporting)
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Mumbai, Maharashtra, India
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May 1, 2023 – October 1, 2023
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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.
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.
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.
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.