Data Analytics Portfolio
Certified Data Analyst professional specialized in campaign and product analytics for the loyalty industry, supporting large customer bases with end-to-end campaign management, reporting, automation, and business-focused analytical solutions.
Based in Dublin, Ireland, I am a data analyst with over four years of experience working across campaign analytics, financial reporting, dashboard development, and process automation.
My background combines SQL, Excel, Power BI, Tableau, Python, Snowflake, Azure, and Power Automate to analyse large datasets, optimise reporting processes, and translate data into clear insights for business stakeholders.
At Tata Consultancy Services and Mu Sigma, I supported campaign performance analysis, A/B testing, KPI reporting, financial analysis, and dashboard automation. My work included reducing reporting effort, improving query performance, automating recurring tasks, and presenting decision-ready insights.
I recently completed my M.Sc. in Computing, Data Analytics at Dublin City University, and I am currently seeking opportunities in Ireland as a Data Analyst, Campaign Analyst, Financial Analyst, or Reporting Analyst.
SQL, Excel, KPI tracking, campaign analysis, product analysis, financial analysis, trend analysis, and business reporting.
Power BI, Tableau, dashboard design, performance reporting, executive summaries, and insight communication.
Python, Snowflake, Power Automate, Power Query, Azure, SQL procedures, scheduled workflows, and process improvement.
Improved analytical performance and reporting efficiency by combining faster SQL processing with clearer business dashboards for stakeholder decision-making.
Delivered measurable campaign reporting improvements by reducing manual effort, increasing customer engagement, and automating repeat analytical workflows.
Why this project started: Recurring campaign targeting and reminder activities involved repeated manual effort, higher turnaround time, and avoidable dependency on repetitive operational steps.
What was achieved: Built an automated process using stored procedures and scheduled tasks to streamline recurring campaign operations, reduce manual effort by 15%, and improve consistency in execution.
Why this project started: Stakeholders needed faster visibility into campaign, sales, and operational KPIs without waiting for manually prepared reports.
What was achieved: Created an interactive KPI dashboard that improved visibility, reduced reporting delays, and supported faster data-driven decision-making.
Why this project started: Campaign teams needed a more evidence-based way to identify which targeting and communication strategies were performing better.
What was achieved: Evaluated campaign variants, measured uplift, and supported improved targeting decisions that contributed to a 10% increase in customer engagement.
Why this project started: Financial reporting and business valuation work required a more structured and efficient process to reduce turnaround time and improve reliability.
What was achieved: Improved reporting efficiency by 25% by streamlining data transformation, reducing manual work, and producing more structured outputs for business reviews.
Problem: In Ireland, rental listings can create difficulties for both genuine tenants and responsible landlords. Tenants often face high rents, delayed repairs, weak property maintenance, and situations where landlords may not be registered with the RTB. At the same time, landlords and agents also need a better way to identify suitable tenants based on fit, reliability, and mutual expectations.
Idea: Build a rating and matching platform connected to rental-style listing workflows, where property posts are shown only to applicants who match the landlord’s criteria and where tenant and landlord ratings improve transparency on both sides.
Goal: Create a fairer and more data-driven rental ecosystem that reduces exploitation, improves trust, and helps both tenants and landlords make better decisions before entering an agreement.
Status: Initial case study idea. Approach, tools, data model, and implementation plan will be added later.
Dublin City University | Dublin, Ireland | Graduated Nov 2024
Completed postgraduate study focused on data analytics, structured data processing, analytics-driven problem solving, and practical application of modern analytical techniques.