KC

Senior Data Scientist · Banking Pricing · AI · Auckland, New Zealand

Turning pricing, AI, and customer intelligence into business decisions.

Kevin Chang helps financial services leaders connect advanced modelling with revenue, customer outcomes, conduct risk, and clear executive action.

12+ yrs analytics

Experience

Pricing + P&L

Commercial focus

1,200+ citations

Research reach

60+ institutions

Adoption

Pricing strategy Customer outcomes Model risk Executive decisions
Data Science Retail Banking Pricing Strategy Machine Learning AI / GenAI Customer Analytics
Experience evidence Project proof Printable resume LinkedIn

Professional Snapshot

What recruiters should know first.

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.

Current role

Senior Data Scientist

ASB Bank · Auckland, New Zealand

Experience

12+ years turning models into decisions

Financial services, government policy, consulting, and research delivery with a consistent focus on usable decision support.

Banking focus

Pricing work connected to P&L, customer outcomes, and risk

Current ASB focus spans pricing models, product performance, conduct considerations, and post-launch optimisation.

Customer intelligence

Customer growth and retention modelling

Customer lifetime value, segmentation, churn prediction, and recommendation systems translated into business planning.

AI capability

ML and GenAI with practical guardrails

Predictive analytics plus LLM analysis of open-ended survey responses, customer sentiment, and signal extraction.

Risk discipline

Model assurance background

Validation experience across risk, credit, and operational models with regulatory expectations.

Leadership

Executive-ready communication and mentoring

Turns technical complexity into clear recommendations for senior stakeholders while building analytics capability in teams.

Career Evidence

Senior analytics work, made easy to scan.

A progression across ASB Bank, New Zealand Treasury, and statistical consulting, with a through-line of rigorous modelling, stakeholder clarity, and practical data products.

Jan 2026 — Present

Senior Data Scientist

ASB Bank

Auckland, New Zealand

Role brief

Lead pricing strategy by integrating market intelligence, competitor dynamics, and advanced analytics to drive revenue growth and competitive positioning.

Pricing Analytics Revenue Optimisation Advanced Statistical Modelling

Evidence

  • 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.
Jan 2023 — Jan 2026

Data Scientist

ASB Bank

Auckland, New Zealand

Role brief

Lead strategic analytics initiatives, drive customer growth, and business innovation across the bank.

Customer Intelligence LLM ML Data Products

Evidence

  • 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.
Jan 2021 — Jan 2023

Model Assurance Specialist

ASB Bank

Auckland, New Zealand

Role brief

Provided independent, rigorous validation of critical bank-wide models to ensure regulatory compliance and risk management.

Model Validation Risk Regulatory Compliance Advanced Statistical Modelling

Evidence

  • 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.
Jan 2019 — Jan 2021

Modelling Analyst

The New Zealand Treasury

Wellington, New Zealand

Role brief

Developed sophisticated analytical tools supporting government policy development and fiscal planning.

Microsimulation Policy R Shiny Government

Evidence

  • 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.
Jan 2014 — Jan 2019

Statistical Consultant

Statistical Consulting Centre, University of Auckland

Auckland, New Zealand

Role brief

Delivered end-to-end analytical consulting solutions across academia, government, and industry, building custom solutions for complex statistical challenges.

Consulting R Statistics Training

Evidence

  • 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.

Portfolio Proof

Data products with policy and business weight.

Public work selected for one reason: it shows end-to-end delivery from problem framing and modelling through to usable tools, adoption, and decision impact.

Featured case studies

2026 Policy model
Case study

Simulation Modelling for A Better Start

Simulation model evaluating how early-life interventions in literacy, growth, and wellbeing influence long-term and equitable outcomes. Models life-course impacts and delivers results through an interactive Shiny web app.

Problem
Policymakers needed to see how early-life interventions in literacy, growth, and wellbeing shape long-term and equitable outcomes.
Approach
Built a life-course microsimulation model and delivered it to non-technical users through an interactive Shiny web app.
Impact
Lets MoE / COMPASS stakeholders test intervention scenarios and equity impacts before committing policy.
RShinyMicrosimulationMoE
2026 AI system
Case study

Multi-Asset LLM Trading Bot

Personal AI-agent systems project combining a 3-stage LLM decision pipeline with quantitative risk controls, market-regime features, CI/CD, and a read-only monitoring dashboard.

Problem
Agentic decision systems need clear controls, observability, and failure boundaries before they can be trusted with live actions.
Approach
Built a 3-stage LLM pipeline over a quant stack (LightGBM, GARCH volatility, HMM regime detection), with mechanical exits, circuit breakers, and monitoring.
Impact
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.
PythonLightGBMGARCHHMMDocker
2026 AI system
Case study

Personalised Daily Briefing Bot

Self-scheduling Telegram bot delivering three personalised briefings per day. Learns user interests via an evolving memory store and flags statistical anomalies (IQR-based) in NZ currencies, indices, and bank mortgage and term-deposit rates. ~$0.03/day running cost.

Problem
Staying on top of NZ news, markets, and bank rate moves means scanning many sources every day.
Approach
Self-scheduling Telegram bot with an evolving memory store and IQR-based anomaly detection across currencies, indices, and bank mortgage / term-deposit rates.
Impact
Three personalised briefings a day at ~$0.03/day running cost; runs in Docker on a NAS with no external scheduler.
PythonDockerOpenRouterSQLiteTelegram
2021 Decision app
Case study

Automated Psychometrics

R Shiny application enabling 60+ educational institutions to conduct reproducible psychometric analyses without coding knowledge. Published in PLoS ONE (1200+ citations) and adopted by major NZ assessment organisations.

Problem
Reproducible psychometric analysis (Rasch, DIF, equating) required specialist coding, putting it out of reach for most assessment teams.
Approach
Built an open-source R Shiny app exposing the full reproducible workflow through a no-code interface; peer-reviewed and published in PLoS ONE.
Impact
Adopted by 60+ educational institutions worldwide; 1,200+ citations.
RShinyRasch AnalysisPsychometrics

Additional public work

2021 Dashboard

COVID-19 Case Trends Visualisation

Interactive Highcharter visualisation of pandemic trends, used by NZ media and health communications to inform public understanding of outbreak dynamics.

RShinyHighcharterData Journalism
2021 Policy model

Income Explorer

The Income Explorer is an interactive app that models the relationship between wages and disposable income, assessing the impact of the New Zealand tax and welfare system on family incomes and work incentive indicators like effective marginal tax rates.

RShinyNZ Treasury
2019 Policy model

Vulnerable Children Investment Approach

Integrated IDI administrative data to identify causal pathways from family violence to child outcomes. Findings informed $50M+ policy investment decisions on prevention and support interventions.

RIDICausal InferencePolicy Research
2018 Policy model

Child Wellbeing Knowledge Laboratory

Microsimulation platform analysing 50+ policy interventions to identify high-impact factors for child wellbeing. Interactive tool used by 20+ NZ government policy teams.

RShinyMicrosimulationMBIE
2018 Research tool

Pacific Aid Donor-Recipient Mapping

Network analysis and visualisation of Pacific region development aid flows, informing NZ foreign aid strategy and regional partnership priorities.

RShinyNetwork AnalysisMFAT

Capability Map

Technical depth with commercial context.

Skill groups are organised for recruiters and hiring leaders: what Kevin can do, where it applies, and how it shows up in banking, pricing, analytics, and AI work.

AI / ML / GenAI

Prediction, language-model analysis, and customer intelligence use cases.

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

Pricing / Banking / Optimisation

Commercial analytics connected to revenue, margin, customer outcomes, and governance.

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

Data Engineering / Analytics Platforms

Reusable data products and analytics surfaces that business teams can actually use.

SQL Snowflake Databricks dbt Shiny dashboards Data products Git

Programming / Modelling

Statistical depth for simulation, experimentation, and reproducible analysis.

R Python Advanced statistical modelling Microsimulation Experimental design Data visualisation

Communication / Stakeholder Impact

Clear recommendations for senior stakeholders, technical peers, and delivery teams.

Executive insight translation Stakeholder communication Mentoring Research Consulting

Credibility Proof

Research, publications, and analytical rigour.

Peer-reviewed and thesis work that supports Kevin’s technical credibility without overwhelming the main career story.

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.
  • 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.
  • 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.
  • Mackenzie, B. W., Chang, K., Zoing, M., Jain, R., Hoggard, M., Biswas, K., Douglas, R. G., & Taylor, M. W. (2019). Longitudinal study of the bacterial and fungal microbiota in the human sinuses reveals seasonal and annual changes in diversity. Scientific Reports.
2018
  • Lay-Yee, R., Milne, B., Shackleton, N., Chang, K. & Davis P. (2018). Preventing youth depression: Simulating the impact of parenting interventions. Advances in Life Course Research. Microsimulation informing evidence-based youth mental health policy.
  • Courtney, M. G. R. & Chang, K. C. (2018). Dealing with non-normality: An introduction and step-by-step guide using R. Test Journal. Practical statistical guidance for 500+ academic practitioners.
2017
  • Chang, K. (2017). Computer generation of designs for two-phase experiments with applications to multiplex experiments in proteomics [Doctoral thesis, The University of Auckland]. Statistical design methodology with applications in high-dimensional biology. View ↗

Academic Foundation

Education

  • 2017

    Ph.D. in Statistics and Biological Sciences

    University of Auckland

  • 2008

    B.Sc. (Hons) in Bioinformatics

    University of Auckland

  • 2007

    B.Sc. in Bioinformatics

    University of Auckland

Personal Context

Languages

  • English Fluent
  • Mandarin Chinese Fluent

Interests

Running Photography Travelling