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Data Analyst with 1.5 years in SQL, Python, Machine Learning & Data Visualization
Data & BI Analyst with end-to-end experience building analytical pipelines - from SQL data modelling and ELT design to Power BI and Tableau dashboards that turn raw data into decisions. MSc Data Analytics (National College of Ireland) backed by 7 portfolio projects spanning SQL, Python, Machine Learning, and statistical analysis across supply chain, marketing, and customer engagement domains. Known for translating complex analytical findings into structured storyboards, KPI dashboards, and prescriptive reporting that non-technical stakeholders can act on.
National College of Engineering
MSc · Data Analytics
January 17, 2023 – April 11, 2026
Vishwakarma Institute of Technology
B.Tech · Instrumentation and Control Engineering
August 1, 2017 – June 30, 2021
Bidvest Noonan (Client: Mallinckrodt Pharmaceuticals)
Operations Associate
September 1, 2024 – April 1, 2026
Dublin, County Dublin, Ireland
National College of Ireland
Research Lab Intern
October 1, 2023 – March 1, 2024
Dublin, County Dublin, Ireland
Alta Tecnologia Solutions
Junior Front-End Developer
June 1, 2021 – December 1, 2022
Pune, Maharashtra, India
Vendor Pricing & Inventory Profitability Analysis
June 17, 2026 – Present
Surfaced pricing leakages worth ~12% of gross margin and Pareto vendor concentration risks (80/20) across 6 product lines by architecting a relational SQLite data model and running advanced SQL (CTEs, window functions) with Python EDA giving procurement leads their first structured view of which vendors were eroding profitability. Reduced ad-hoc analyst reporting requests by ~60% by delivering self-serve Power BI and Tableau dashboards covering 5 KPI measures (sales contribution, gross profit, stock turnover, order fulfilment accuracy, pricing efficiency) - enabling both technical and non-technical stakeholders to track trends without raising manual requests.
A/B Testing & Conversion Prediction for Marketing Campaigns
June 17, 2026 – Present
Confirmed with 95% confidence that Facebook outperformed Google AdWords on conversion rate across a multi-week campaign dataset using a two-sample t-test framework giving the marketing team a statistically grounded basis to reallocate spend. Achieved R² ~0.76 on a click-to-conversion regression model (scikit-learn, statsmodels); forecasted performance under different spend scenarios and recommended channel-level allocation strategies, with findings delivered in a structured report for non-technical decision-makers.
Supply Chain Analytics & Order Fulfilment Risk Prediction
June 17, 2026 – Present
Modelled an 18% reduction in late shipments by designing an end-to-end ELT pipeline processing 180,000+ global e-commerce orders with distributed PySpark/SparkSQL, isolating carrier delays, warehouse processing time, and demand spikes as the 3 highest-impact fulfilment failure drivers. Achieved 84% precision on order-risk prediction using a Random Forest classifier with SMOTE oversampling to address class imbalance; packaged model outputs and root-cause findings into a storyboarded Power BI deck with prescriptive recommendations, delivered to both executive and technical stakeholders to support operational decisions.
Data Quality & Customer Engagement Analysis - Yelp Dataset
June 17, 2026 – Present
Uncovered engagement trends across 150K+ businesses by integrating 5 JSON datasets of varying formats and sources into a relational SQLite schema via SQLAlchemy, resolving structural quality issues missing values, schema mismatches, and duplicate records to produce a clean, analysis-ready dataset. Engineered a composite business success score using IQR-based outlier removal and weighted multi-metric aggregation across review volume, ratings, and check-in frequency; validated through geo-spatial analysis to surface category-level and neighbourhood-level patterns that support data-driven site selection and investment prioritisation.
View ProjectSentiment Analysis and Prediction in Social Media
IEEE/Scopus indexed
February 1, 2020 – Present
The candidate scored 0% on the technical test, indicating no demonstrated proficiency in the assessed technical skills.
Limitations
Cultural Fit Analysis
The candidate's project diversity, spanning vendor profitability, supply chain, marketing, and customer engagement, indicates a broad interest and adaptability to different business domains. Their experience as a Junior Front-End Developer and Research Lab Intern, alongside their target role as a Data Analyst, shows a willingness to learn and apply skills across various technical areas. The academic nature of most projects, however, suggests a need to validate real-world application and collaboration in a corporate setting. The low psychometric test score could be a concern for cultural fit, particularly regarding team collaboration and work attitude, and warrants further investigation.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical thinking, problem-solving, and communication skills through their project descriptions, particularly in making complex data accessible to non-technical audiences. Their experience in defect triage and maintaining audit-ready records suggests attention to detail and operational reliability. The psychometric test score is low, which might indicate potential areas for development in logical reasoning, work attitude, stress handling, or team collaboration, but this needs further validation.