Available to hire
I’m a data-driven marketer and analyst with a strong foundation in quantitative analysis, digital performance, and customer insights. I help brands interpret their data, optimise campaigns, and build analytics foundations that support long-term growth.
My experience includes building dashboards, conducting segmentation and forecasting, improving reporting workflows, analysing paid/organic performance, running A/B tests, and providing strategic recommendations to marketing and product teams. With a blend of marketing experience and technical analytics skills, I support clients who need clarity, structure, and data they can trust.
Skills
Experience Level
Work Experience
Growth & Marketing Analyst at LUME Jewellery
October 1, 2025 - October 1, 2025Designed and managed the entire digital analytics ecosystem for a multi-channel e-commerce brand, owning reporting, tracking, segmentation, and performance optimisation across all platforms. Hands-on with GA4, Looker Studio, Excel, and platform analytics to track traffic, engagement, conversions, and channel ROI. Regularly used existing dashboards and reporting systems to monitor metrics across channels, drawing insights to support decision-making and campaign optimisation. Analyzed campaign performance across Google Ads, Meta, SEO, and email, identifying optimisation opportunities and contributing recommendations for strategic decisions. Developed segmentation, profiling, and customer insights to support CRM flows and improve engagement. Conducted A/B and creative testing to evaluate messaging, content, and landing page performance, summarising findings for future strategy. Translated performance data into insights for planning and growth initiatives.
Senior Data Analyst at DEMAND FORECAST
November 1, 2024 - November 1, 2024Worked with large, multi-market datasets to support high-stakes operational and commercial planning across NZ and Australia. Operated and optimised a large-scale forecasting system through command-line workflows, triggering automated pipelines for data extraction, cleaning, feature engineering, model execution, accuracy checks, and dashboard output. Maintained and improved 70+ time-series forecasting models, reducing errors and strengthening overall accuracy by continuously diagnosing anomalies, validating outputs, and adjusting model parameters. Cleaned, validated, and imported large datasets using SQL and Python, then analysed performance trends across millions of data points to identify behavioural patterns and anomalies. Translated complex model behaviour into clear, actionable insights for executives, product teams, marketers, and operations — adapting communication for both technical and non-technical audiences. Partnered with cross-functional stakeholders (analytics, product,
Education
Conjoint Bachelor of Commerce & Bachelor of Arts in Marketing & Statistics at The University of Auckland
January 11, 2030 - January 1, 2022Qualifications
Industry Experience
Retail, Software & Internet, Professional Services, Education, Media & Entertainment
Skills
Experience Level
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