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Kevin Chang

Senior Data Scientist | Banking Pricing, AI & Customer Intelligence

Auckland, New Zealand kevin.ct.chang@gmail.com linkedin.com/in/kevin-ct-chang github.com/kcha193

Data science leader delivering measurable business impact: 12+ years driving revenue growth, customer value, and strategic decision-making through advanced analytics, machine learning, and data products. Currently at ASB Bank optimising pricing strategy and driving customer intelligence initiatives. Rare combination of commercial expertise, technical depth, and policy modelling knowledge—proven ability to translate complex models into clear, actionable insights for C-suite stakeholders. Specialist in customer lifetime value systems, predictive analytics, generative AI applications, and large-scale microsimulation. Recognised mentor building high-performing analytics teams. Experience spans financial services, government policy, and consulting.

Banking pricingAI / MLCustomer intelligenceModel riskExecutive insight
Professional Experience
Senior Data Scientist — ASB Bank, Auckland, New Zealand Jan 2026 – Present
  • Drive continuous improvement of pricing strategies, models, and processes to enhance customer experience and business performance.
  • Develop and implement pricing models and analytical frameworks to support new product features or enhancements aligned with customer and market needs.
  • Monitor product performance, including pricing impact on revenue, profitability, and customer outcomes, and provide actionable insights to optimise P&L performance.
  • Apply simulation-based analytical frameworks—drawing on a background in large-scale policy microsimulation—to model the distributional impact of pricing changes across customer segments before deployment.
  • Evaluate post-launch performance using advanced analytics, recommending adjustments to pricing, product features, and customer strategies to improve outcomes.
  • Identify, assess, and proactively manage risks associated with pricing decisions, including regulatory, conduct, and model risks.
Data Scientist — ASB Bank, Auckland, New Zealand Jan 2023 – Jan 2026
  • Customer Intelligence & Growth: Developed and deployed predictive models for customer lifetime value, segmentation, churn prediction, and product recommendation, delivering actionable insights that inform strategic planning and drive measurable revenue growth.
  • Generative AI: Applied large language models (LLMs) to analyse open-ended survey responses, identifying common themes and customer sentiments driving NPS results and customer experience insights.
  • Data Product Leadership: Partner with product, design, and engineering teams to build scalable insights platforms and analytics tools that enable data-driven decision-making across business units.
Model Assurance Specialist — ASB Bank, Auckland, New Zealand Jan 2021 – Jan 2023
  • Conducted comprehensive end-to-end validations of risk, credit, and operational models, assessing methodology, data quality, implementation, and ongoing performance monitoring.
  • Challenged model assumptions and methodologies through rigorous statistical analysis, identifying limitations and recommending enhancements that strengthened model reliability.
  • Collaborated with model developers, risk managers, and senior stakeholders to ensure models met regulatory standards (RBNZ/APRA requirements) and internal risk policies.
  • Delivered clear, comprehensive validation reports to senior management and governance committees, facilitating informed decision-making on model approval and risk mitigation.
Modelling Analyst — The New Zealand Treasury, Wellington, New Zealand Jan 2019 – Jan 2021
  • Policy Impact Modelling: Built and maintained microsimulation models to analyse tax and welfare policy impacts, directly informing Budget decisions and Ministerial recommendations.
  • Data Integration & Engineering: Integrated complex survey and administrative datasets (IDI, HES) to create robust analytical foundations for policy evaluation.
  • Product Development: Created interactive R Shiny dashboards and internal R packages that streamlined policy analysis workflows and improved accessibility of insights for policy analysts.
  • Stakeholder Collaboration: Worked closely with policy teams, Statistics NZ, and other government agencies to ensure analytical outputs aligned with strategic policy objectives.
Statistical Consultant — Statistical Consulting Centre, University of Auckland, Auckland, New Zealand Jan 2014 – Jan 2019
  • Provided statistical expertise to 60+ clients across academic, government, and commercial sectors, translating business questions into rigorous analytical approaches.
  • Designed and deployed web-based analytical tools and custom R packages for clients, including government agencies and research institutions.
  • Conducted advanced analyses spanning experimental design, survey methodology, longitudinal modelling, and causal inference.
  • Led R programming workshops and training sessions, building analytical capability among researchers and practitioners.
Selected Projects

Simulation Modelling for A Better Start

Lets MoE / COMPASS stakeholders test intervention scenarios and equity impacts before committing policy.

R · Shiny · Microsimulation · MoE

Multi-Asset LLM Trading Bot

944-test suite, CI/CD auto-deploy to a self-hosted NAS, read-only dashboard, and layered risk gates for BTC / ETH / SOL spot execution.

Python · LightGBM · GARCH · HMM · Docker · OpenRouter · Binance API · FastAPI · Telegram

Personalised Daily Briefing Bot

Three personalised briefings a day at ~$0.03/day running cost; runs in Docker on a NAS with no external scheduler.

Python · Docker · OpenRouter · SQLite · Telegram

Automated Psychometrics

Adopted by 60+ educational institutions worldwide; 1,200+ citations.

R · Shiny · Rasch Analysis · Psychometrics

Core Skills

AI / ML / GenAI

Machine learning, Predictive analytics, Generative AI / LLMs, LLM survey & sentiment analysis, Churn prediction, Customer segmentation, Product recommendation

Pricing / Banking / Optimisation

Pricing strategy, Revenue optimisation, Customer lifetime value, Customer intelligence, Model assurance & validation, Regulatory model risk

Data Engineering / Analytics Platforms

SQL, Snowflake, Databricks, dbt, Shiny dashboards, Data products, Git

Programming / Modelling

R, Python, Advanced statistical modelling, Microsimulation, Experimental design, Data visualisation

Communication / Stakeholder Impact

Executive insight translation, Stakeholder communication, Mentoring, Research, Consulting

Selected Publications

2021. Courtney, M. G. R., Chang, K., Mei, E., Meissel, K., Rowe, L., & Issayeva, L. (2021). autopsych: An R Shiny Tool for the Reproducible Rasch Analysis, Differential Item Functioning, Equating, and Examination of Group Effects. PLoS ONE. Open-source tool adopted by 60+ educational institutions globally; 1200+ citations.

2019. Shackleton, N., Chang, K., Lay-yee, R., D'Souza, S., Davis, P., & Milne, B. (2019). Microsimulation model of child and adolescent overweight: making use of what we already know. International Journal of Obesity. Policy modelling supporting NZ child health intervention strategies.

2019. Zhao, J., Mackay, L., Chang, K., Mavoa, S., Stewart, T., Ikeda, E., ... & Smith, M. (2019). Visualising combined time use patterns of children's activities and their association with weight status and neighborhood context. International Journal of Environmental Research & Public Health.

2019. Sutherland, K., Clatworthy, M., Chang, K., Rahardja, R., & Young, S. W. (2019). Risk factors for revision anterior cruciate ligament reconstruction and frequency with which patients change surgeons. Orthopaedic Journal of Sports Medicine.

+ 4 further peer-reviewed publications — full list at kevin-cv.netlify.app/#publications

Education
Ph.D. in Statistics and Biological Sciences — University of Auckland 2017
B.Sc. (Hons) in Bioinformatics — University of Auckland 2008
B.Sc. in Bioinformatics — University of Auckland 2007