Adelaide, South Australia, Australia
An Economics graduate with a strong analytical mindset, I am currently expanding my expertise in data-driven decision-making through a Master’s in Business Analytics at the University of Adelaide — a leading Go8 university ranked among the top 100 globally. My passion for deciphering data narratives, honed through my academic journey and professional experience as a Business Analyst in the tech sphere, has provided me with a solid foundation in statistical analysis and data visualisation. I thrive in dynamic environments, leveraging these skills to translate complex data into actionable business strategies and contribute to innovative projects at the intersection of economics and technology.
As a Lead Business Analyst, I drove end-to-end delivery of customer-facing digital products for international clients across the US market. I collaborated closely with product, UX, and engineering to translate complex requirements into actionable user stories, process flows, and solution concepts. I led a cross-functional team of 8+ developers and QA engineers, maintaining a 100% on-time sprint delivery rate using agile best practices. Leveraging SQL, Python, and Power BI, I built data models, designed ML-enhanced dashboards, and applied A/B testing, customer segmentation, and regression-based insights to improve decision-making and optimize product performance. I also drove major system migrations (100k+ records), reducing data redundancy by 30% and automating workflows to cut manual effort by 40%. My leadership strengthened stakeholder alignment, product clarity, and continuous improvement across all projects.
As a Business Analyst at Ilsa Interactive, I worked across multiple client projects to streamline operations through data-driven problem-solving. I conducted extensive SQL-based data extraction, exploratory analysis, and root-cause investigation to identify process gaps and reduce operational inefficiencies. I designed end-to-end test plans, performed UAT, and integrated third-party systems, eliminating manual workflows and cutting redundancy by 30%. Supporting agile delivery, I contributed to backlog refinement, sprint planning, and requirement workshops while documenting clear user stories and acceptance criteria. My work directly improved data accessibility, system performance, and team productivity across logistics, e-commerce, and portfolio management products.
As a Teaching Assistant for a 300-level course: Quantitative Research Methods, I gave 15+ tutorials on IBM SPSS, regression analysis, and statistical methods to a class of over 40 students, breaking down complex concepts into clear, practical insights. I provided individual mentoring to students during the semester, guiding them in refining their data analysis skills and improving their coursework by keeping additional office hours. Apart from that, I supported the professor by grading 100+ assignments and research papers, ensuring accuracy, fairness, and consistency in evaluations. Through my teaching and mentoring, I helped students to not only develop a strong critical mindset but also build their confidence in applying quantitative techniques
I conducted a comprehensive valuation of Artistic Denim Mill by benchmarking it against 17 prominent textile industries listed on the Pakistan Stock Exchange (PSX). My approach involved an in-depth analysis of income statements, balance sheets, and cash flow statements for each company, culminating in the development of a sophisticated financial model to assess Artistic Denim Mill's financial standing. Leveraging my expertise, I calculated a spectrum of key multiples including P/E, Sales/Share, EBITDA/Share, and Book Value/Share. Through this meticulous process, I derived the optimal share price for Artistic Denim Mill, enabling me to make informed predictions regarding the stock's valuation. This analytical endeavor not only provided insights into the company's financial health but also allowed me to ascertain whether the stock was undervalued or overvalued in the market.
As a key contributor in the Vendor Ops department, my primary responsibility centered around automating the weekly targets for two critical Key Performance Indicators (KPIs): Incident Rate (IR) and Vendor Satisfaction (VSAT). In order to achieve this, I wrote complex SQL queries and Python code, not only to extract and clean data but also to conduct in-depth analyses tailored to the specific vertical and case generation. My proactive approach allowed me to systematically identify any potential loopholes within the KPIs, empowering my team to implement strategic improvements effectively. Once the data was processed and refined, I transformed it into a visually appealing and easily comprehensible format. Leveraging tools such as Google Data Studios and MS Power BI, I created dynamic dashboards that provided my team with real-time insights into the KPIs, facilitating ongoing tracking and enabling predictive analysis. Through my efforts, I not only automated processes but also enhanced the decision-making capabilities of the team, fostering a more efficient and informed operational environment.
Led the documentation of the marketing strategy and operations for the company, providing actionable insights to enhance business performance. Conducted a thorough GAP and SWOT analysis on the firm’s business tools used to sell its products, identifying key areas for improvement. Performed an in-depth analysis of the textile industry in Pakistan, incorporating international market trends and digital content strategies to inform decision-making. Delivered strategic recommendations that optimized the company’s marketing approach, aligning it with global best practices and ensuring better targeting and positioning in the marketplace.