Experience

Led the design and delivery of a multi-system data integration and analytics platform, doubling system throughput and ensuring stability through three major infrastructure migrations, while acting as the technical link between engineering, operations, and executive stakeholders. Owned operationally critical logic across systems (e.g. unsubscribe flows, financial incentive rules, failed redirect recovery, member portal experience) and built custom interfaces to close workflow gaps. Delivered a production propensity model to predict participant completion, gaining first-hand insight into intervention feedback loops and the complexity of deploying ML in live systems. Also developed and maintained reporting infrastructure (Power BI models, Shiny dashboards, SQL data models) and guided platform roadmap in collaboration with execs.

Honorary position in recognition of professional and academic standing within the university

Associate Lecturer and Associate Fellow of the Higher Education Academy (AFHEA), responsible for designing and delivering undergraduate subjects in statistics and data science, including Probability for Statistics and Data Science and Meta-Analysis (STM4PDS, STA5MA). Led subject coordination, curriculum development, and creative strategies to boost engagement, confidence, and deep learning. Developed technically rigorous, accessible assessments and materials—bridging theoretical understanding with real-world data applications. Regularly integrate contemporary research and best practices in teaching, contributing to academic networks and pedagogical innovation.

Recipient of the Vice-Chancellor's Sessional Teaching Award 2020.

Subjects:

• Meta-Analysis (Master's)
• Applied Statistical Methods (Undergraduate)
• Linear Models (Undergraduate)

Tools and techniques: R, RevMan, Metafor, reviewing published meta-analysis to assess scientific evidence, detect and explain heterogeneity via techniques such as subgroup analysis and meta-regression.

Subject codes: STA5MA, STA3ASM, STA3LM.

Tools: PL/SQL, Oracle SQLPlus, Extended Entity Relationship (EER) modelling for relational database design, normalization.

• Teaching hands-on material to over 150 students in five two-hour labs p/w.
• Fast-paced help sessions, debugging individual code for 40+ students in one hour (what a rush!).
• Create and review SQL and database design assignments.
• Mark roughly 400 student assignments per semester.

Subject codes: CSE2DBF and CSE4DBF

Lead developer and maintainer of R package 'rcosmo' for analysis of cosmological data.

Highly Commended at the Australian Astrostatistics Association 2020 awards.

• Published on the Comprehensive R Archive Network (CRAN).
• Over 13,000 downloads on CRAN (with currently over 150 per week).
• Manuscript published in the R Journal.
• Funded in part by an Australian government research grant.

Probability and statistics applied to engineering problems.

Subject code: STM2EPS

Instructor and course author for the New Zealand Social Statistics Network at the University of Auckland, delivering a four-day intensive course on SQL and the Integrated Data Infrastructure (IDI). Delivered the course over 14 times to academic and professional audiences in government, research, and social science. Wrote the accompanying course textbook, designed for clarity, accessibility, and real-world data application. Consistently achieved 5-star student experience ratings. Strong focus on empowering non-technical professionals to work effectively with complex data systems, query design, and relational thinking—experience that informs my broader interest in technical enablement, infrastructure, and education.

Statistical consulting / contract work on survey design and analysis, in Politics and International Relations.

Project: Mobilising Insights in Defence and Security (MINDS) study, Canada, with Prof Maria Rost Rublee.

Project 2: May 2021

In partnership with the Nuffield Department of Medicine, University of Oxford, International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC). Testing and developing algorithms for diagnosing acute kidney injury and acute kidney disease, using serum creatinine levels, in a global observational study.

Publication outcomes:

1. ISARIC Clinical Characterization Group., Garcia-Gallo, E., Merson, L. et al. ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19. Sci Data 9, 454 (2022).
2. Wainstein M, MacDonald S, Fryer D, Young K, Balan V, et al. (2022) Use of an extended KDIGO definition to diagnose acute kidney injury in patients with COVID-19: A multinational study using the ISARIC–WHO clinical characterisation protocol. PLOS Medicine 19(4): e1003969.

Project 1: April 2019.

In collaboration with the University of Montreal, Canada. Exploring models for transdiagnostic clustering of digital phenotypes for predicting clinical psychiatric prognoses from passive sensing with smart-phones. Developed the R package 'studentlife' for tidy handling, navigation and exploratory data analysis of a valuable mobile-health data set. Published associated bulletin in the Journal of Open Source Software.

Support / drop-in sessions for students on their capstone data science project: an open-ended project for star students to demonstrate and hone their data science stack.

Master's of Data Science Capstone Project DATA7901 and DATA7903.

A network of individuals with executive leadership experience in university clubs and societies. As a Senior Mentor I was available to pass on lessons-learned from my own challenges and successes in leadership.

Research paper and conference presentation + fun networking with some of Australia's brightest maths and stats students.

My project investigated the asymptotic properties of functionals of long range dependent random fields and processes.

Providing safety and emergency response for recreational divers touring the great barrier reef.