From 2023–2024, I contributed to Leftbrain’s AI image recognition system, an IoT-powered platform to optimise ice cream stock management, addressing inefficiencies in freezer monitoring for manufacturers. As a data analyst and product tester, I evaluated system performance, conducted Excel-based analyses, and supported product testing and deployment in freezers. My methods included analysing freezer door openings, photo-based stock accuracy, correlations between stock levels and door openings, hourly purchase distributions, and overall sales trends. Findings revealed improved stock accuracy metrics and actionable insights, enhancing freezer management efficiency and supporting Leftbrain’s scalability across independent distribution channels.
In 2021, I analysed the New Zealand Defence Force (NZDF) Pulse Workforce Survey at Allen + Clarke to provide data-driven insights into workplace culture, supporting organisational improvements in health, satisfaction, and retention. As a data analyst, I performed statistical analyses and contributed to six reports, processing responses from over 5,000 participants. My methods included descriptive statistics, regression analyses of outcomes like morale, job satisfaction, and leadership, and qualitative coding of two open-ended questions, segmented by gender, service type, and rank. Findings identified priorities for inclusivity, organizational purpose, and work-life balance, guiding NZDF’s strategies to enhance workforce commitment.
In 2022, I analysed qualitative data from Te Tari Taiwhenua’s Whakahoki Kōrero: Your Feedback Survey, commissioned by the Department of Internal Affairs. In collaboration with another key analyst, we used NVivo and Excel to conduct thematic analysis on 1,400+ responses to four open-ended questions, identifying key themes like bullying, exclusion, and valued aspects (people, flexible work). Sub-themes on leadership, diversity, and Māori inclusion emerged, guiding data-driven recommendations to improve IT, staffing, and cultural responsiveness. Data was visualised and graph in Excel for the final report. The analysis provided actionable insights, enhancing workplace culture and supporting Te Tari Taiwhenua’s commitment to equity and employee wellbeing.
In 2025, I undertook a personal data analysis project on coffee shop data. In this scenario the coffee shop struggled to manage staffing and inventory without clear sales patterns. I analysed transactional data using MySQL, SQL, and Excel, building a Metabase dashboard to visualise peak hours and top-selling products. The analysis revealed 8–10 AM as peak sales time, with coffee and tea outperforming other items. Recommendations to increase morning staffing and prioritise high-demand products reduced wait times and waste.
In 2025, I undertook an analysis for a dental SaaS company that was interested in identifying identify high-potential leads in Vienna, Berlin, and Zurich. I scraped dentist data using Python and Google Maps API, analysed it in Excel and Power BI, and created an interactive Power BI dashboard to map dentist distribution and forecast revenue. Berlin showed the largest dentist population, with a potential $136K monthly revenue from 10% lead conversion. Recommendations prioritised marketing in Berlin and tailored SaaS features to regional needs.
A a side project in 2025, I analysed Pokémon data. The problem is that for most Pokémon players, they lack insights into stat trends and type effectiveness for competitive team building. Using Python, MySQL, and Power BI, I analysed Pokémon data across generations, identifying top-performing non-legendary teams (e.g., Ash-Greninja, Mega-Garchomp). Dragon types led with the highest average stats, with Arceus (Mythical) and Slaking (Normal) topping their categories. A Metabase dashboard visualised matchups and type advantages. Recommendations focused on Dragon/Steel teams and Mega evolutions for competitive play, empowering players with data-driven strategies to optimise team performance.
In 2022, I evaluated the social impacts of New Zealand Sign Language (NZSL) Week for the Ministry of Social Development, seeking to enhance public awareness and inform future contracting for this inclusive initiative. I led the evaluation at Allen + Clarke with Dr Greg Martin using a mixed-methods approach: document reviews, stakeholder interviews, and a nationally representative survey to assess NZSL recognition and engagement. Results showed increased awareness (450,000 reached) and interest in learning NZSL, with recommendations for year-round social media promotion and participatory strategies to strengthen impact.
In 2022, I co-led qualitative analysis for a Ministry of Foreign Affairs and Trade (MFAT) commissioned evaluation of the Strengthening Pacific Labour Mobility Programme at Allen + Clarke. Using NVivo, I coded and thematically analysed 86 stakeholder interviews and case study data from Samoa, Solomon Islands, and Kiribati, identifying themes on capacity building, worker wellbeing, and COVID-19 adaptations. Excel supported data synthesis. Findings highlighted effective labour sending unit support but sustainability gaps. Data-driven recommendations, including reintegration support and pastoral care frameworks, shaped MFAT’s programme redesign, enhancing equitable labour mobility outcomes for Pacific workers. You can read it here.
In 2022, I led data analysis for a mixed-methods study at Allen + Clarke for the Australasian College for Emergency Medicine (AECM, examining rising mental health presentations in New Zealand emergency departments (EDs). Collaborating with Dr. Greg Martin, I analysed survey data from 27 ACEM fellows and 30 nurses, conducted thematic coding of 12 stakeholder interviews, and synthesised a literature review of 17 care-models. My methods included descriptive statistics, qualitative coding, and trend analysis. Findings revealed resourcing gaps and inconsistent care models, informing recommendations for specialist staffing, cultural training, and joint pathways to enhance ED care. You can read it here.
In 2021, I conducted data analysis for a Whangārei District Council-commissioned report at Allen + Clarke, evaluating the social harms and benefits of Class 4 gambling (pokies). I analysed datasets from the Department of Internal Affairs, Statistics NZ, and the Health and Lifestyles Survey in Excel, producing visualisations (e.g., expenditure graphs) and updating the report. Findings revealed high gambling expenditure ($810M nationally in 2020) concentrated in deprived areas, exacerbating harms like problem gambling, while noting benefits like community grants. The analysis informed policy options to balance harm reduction with community funding.
In 2022, I led data analysis for an evaluation of a New Zealand HIV and STI self-testing service at Allen + Clarke, assessing equity and scalability for the Burnett Foundation. As team lead, I guided quantitative and qualitative analyses, including thematic coding of 10 key informant interviews and three case studies in NVivo, and quantitative analysis of Burnett Foundation client data (2019–2022). As part of the analysis, we used QGIS to map test kit distribution by postcode, analysing uptake, demographics, and remote area access. Findings identified inequities in geographic and ethnic access, providing data-driven recommendations to enhance outreach and scale equitable self-testing services.
In 2022, I analysed data for an evaluation of a Critical Care Nurses Recruitment Campaign at Allen + Clarke, commissioned by Te Whatu Ora to address New Zealand’s nursing shortage during the COVID-19 pandemic. As a lead analyst, I conducted interviews, performed quantitative and qualitative analyses, and wrote the report. My methods included descriptive statistics on application, referral, and hire metrics, social media engagement analysis, survey data processing, and thematic coding of interview responses. Insights revealed campaign effectiveness and delivery gaps, providing data-driven recommendations to optimise future recruitment efforts for critical care nurses.
In 2019, I analysed data for my Honours dissertation at the University of Waikato, investigating positive psychological resources (self-efficacy, optimism, hope, resilience) among 31 Hamilton, NZ firefighters to support their mental health under workplace stress. As the sole analyst, I designed an online survey and performed statistical analyses to assess positivity ratios and psychological capital across operational and non-operational settings. My methods included correlation analysis, hypothesis testing to compare settings, and regression models identifying optimism and hope as predictors of positivity. Findings showed stronger psychological capital in operational settings, providing data-driven insights to guide Fire and Emergency NZ’s mental health strategies.
In 2022-2023, I supported data analysis for the Royal New Zealand College of General Practitioners’ 2022 Workforce Survey at Allen + Clarke, examining GP demographics, work patterns, attitudes, and retirement intentions. I tested and refined the survey, analysed responses from over 3,500 GPs, and co-wrote the overview report. Using descriptive statistics and trend analysis, we identified inequities (e.g., under representation of Māori/Pacific GPs, gender pay gaps) and workforce challenges (e.g., 37% planning retirement within five years). Findings informed College strategies to address burnout and enhance health equity.
In 2019, for a graduate research methods class, I analysed data from 290 participants using the Five Facets Mindfulness Questionnaire (FFMQ) and Depression, Anxiety, and Stress Scale (DASS) in IBM SPSS. I conducted descriptive statistics, correlations, regression, factor analysis, ANOVA, t-tests, and reliability analysis to explore mindfulness’ impact on psychological distress. Key findings showed non-judgmental mindfulness strongly predicted lower depression scores, and younger participants (17–20) reported higher anxiety. Results informed mental health research, highlighting mindfulness as a protective factor against distress.