Women in Data Science Wellington

Agate Ponder-Sutton

Agate has been doing data science, with and without that title, in industry and academia for slightly less than twenty years. In that time, she has authored and co-authored numerous papers on subjects as diverse as air-quality, brain science, invasive species, and winemakers.  Despite the broad range of subject matter much of Agate’s work (even in the corporate environment) has had real-world benefits for people, and she has found that every dataset has multiple stories to tell.

Agate has an MSc in Applied Mathematics from the University of New Mexico and did post-graduate research at Canterbury University. She has worked for Los Alamos National Laboratory as a research fellow, and as a mathematical modeller for the National Institute for Water and Atmosphere (NIWA). She co-authored the 2018 NZBIE Innovation award-winning “SKOMOBO” project for cheaper school environment monitoring and has also co-authored a paper with the New Zealand Brain Institute. Teaching post-graduate courses and mentoring junior data scientists has been a gratifying challenge where both she and the learners have learnt a lot. She has been told her enthusiasm for her field is contagious.

Agate was thrilled to sit on the panel for Women in Data Science in 2018 and is excited to speak in 2019 as she believes it is important to make a positive difference as a data scientist. Agate is particularly interested in making people aware of what data science is, and in supporting junior ‘data wranglers’ as they navigate the industry. In her spare time, Agate is a history nerd and also teaches sword work and belly dance.

Amanda Hughes

Amanda is a Senior Data Scientist with Nicholson Consulting. Prior to this she has held statistical and analytical roles within government. She is passionate about evidenced based decision making, with an emphasis on communication and implementation. More recently she has been interested in the idea of data ethics and along with other members of the Nicholson Consulting team has helped develop best practices related to algorithm ethics.

Since the last WiDS event, Amanda and the Nicholson Consulting team have successfully implemented a frontline automated decision making algorithm at ACC. She has also attended an AI for Government conference in Toronto where one of the main topics was data ethics.

Dame Diane Robertson

Diane is a successful social sector entrepreneur, giving her a unique combination of strong business and financial skills with strong social sector credentials. She has written and managed databases for a variety of businesses and agencies.

Dame Diane is a former City Missioner at the Auckland City Mission. She designed the Family 100 Research project and was responsible for the collation and analysis of data gathered from the participants. This has become one of New Zealand’s leading authorities on families living in poverty.

Working with Statistics New Zealand, Diane led a project to add Auckland City Mission data to the Integrated Data Infrastructure (IDI). Her passion is to deliver better outcomes for New Zealanders through the development of sound policies informed by qualitative and quantitative data

Donna Cormack

Donna is a Senior Research Fellow, Te Rōpū Rangahau Hauora a Eru Pomare, University of Otago, Wellington and is also associated with Te Kupenga Hauora Māori, University of Auckland.

Emma Vitz

Emma is an actuarial analyst at Finity Consulting in Auckland. She graduated from Victoria University in 2017 with a Bachelor in Science in Statistics and Psychology. Emma is particularly interested in the application of data science, analytics and machine learning to the insurance industry. She has been involved in several projects involving geospatial analysis such as predicting flood in New Zealand, and seeks to continue developing her geospatial skills and applying them to natural perils, climate change analysis and other geospatial projects.

Ernestynne Walsh


Ernestynne is an experienced senior data scientist from the East coast (Ngāti Porou and Te Whānau-ā-Apanui) of Aotearoa, New Zealand. Her speciality areas include: creating transparency in analytics, creating frontline operational analytical models in Government, focussing on the privacy and ethics around predictive modelling and explainable algorithms

This year she has co-presented a keynote about automating frontline decision making at ACC and co-delivered a natural language processing workshop with MIT staff.

She has been appointed as an external member of the ACC Ethics Panel and will be travelling to the United States to deliver a workshop on combining open source and proprietary software.

Fiona Thomson

Fiona is the Analytics Manager at the Social Investment Agency. She is an accomplished data and analytics professional with over 15 years’ experience leading analytics teams in government and the commercial sector. Fiona’s strengths lie in Data Management, Data Infrastructure and Applied Statistics.  Fiona’s passion is developing strategies to maximise insights and outcomes from untapped data sources.

Fiona started her career as an economic statistician working for Statistics New Zealand.

Prior to joining the Social Investment Agency, Fiona established Datacom Wellington’s Big Data and Data Science capability, in her role of Business Manager of Data and Analytics.  Fiona has also held a range of Data and Analytics management roles at the Ministry for Primary Industries, Insurance Australia Group and Royal Bank of Scotland.

Fiona holds a Bachelor of Commerce with an Economics Major from Otago.

Fiona is a committed mother to her wonderful boy and when not spending time with her family or wrangling analysts she enjoys mountain biking and working in her garden.

Frances Krsinich

Frances is a Principal Analyst in MBIE’s Evidence & Insights team, where she’s currently working in the area of housing and building. She has a background of almost 20 years in official statistics, working as a methodologist and researcher for Stats NZ.  Use of non-traditional data sources for official statistics, for example scanner and online data for price measurement, is her particular area of interest.

Kari Jones

Kari is an experienced senior leader in Data & Analytics with experience across a range of industries. In her current role with Air new Zealand, she is responsible for the strategic application of AI, data science and advanced analytics solutions across the airline’s ground and air operations.

Kari is committed improving the economic prosperity of New Zealand through an organisations’ increased application of emerging technology, data science and artificial intelligence. Kari enables this through her work through her involvement on a number of boards.

Outside of work, Kari has won a European Gold Medal with Wales in Lacrosse as well as placing 6th at the world level. After playing, Kari also coached lacrosse at the elite level, leading New Zealand to the their highest world ranking in 2017 which was 8th.

Kat Greenbrook

Kat is the founder of Rogue Penguin, a data visualisation company in Wellington. She has a background in analytical modelling but after a shift in vocation, focuses on the challenge of data communication. Kat retrained in digital design and uses visualisation as a tool to help businesses tell their data stories.

Kate Kolich

Kate Kolich is the Director of Data Systems and Analytics at the Social Investment Agency, where her team supports data and analytics capability for the social sector by acting as an integrator through the provision of the secure data exchange and developing analytical methods and products to measure outcomes for social wellbeing. 

Kate has over 20 years experience in data and analytics and is the co-ambassador for Women in Data Science Wellington for 2019.  Kate has been involved in the Global WiDS program since 2017 when she was a speaker at Sydney WiDS.  Kate is passionate about creating opportunities for people to thrive and innovate, she is active in promoting women in STEM through her work as a Global Women in Data Science Ambassador where she hosted the inaugural NZ Women in Data Science Conference at The University of Auckland in 2018 .  Kate has been an active member of the MIT Sloan Center for Information Systems Research – Data Research Advisory Board and volunteers as an industry mentor at Victoria University of Wellington.   Kate is described as a role model, trend setter and as ‘having endless energy’ which inspires those around her. She holds a Masters in Information Management from Victoria University of Wellington.

Kathryn Hempstalk

Dr Kathryn Hempstalk has an extensive background in machine learning, artificial intelligence and data science. She studied computer science at Waikato University where she gained a doctorate in 2009. Since then she’s worked as a researcher and data scientist in a variety of industries including farming, computer security, healthcare, finance and e-commerce. Kathryn’s current role is Head of Data and Insights at Trade Me.

Lisa Chen

Dr Lisa Chen is a highly qualified and experienced data scientist. As Chief Analytics Officer, Lisa provides analytical leadership at Harmonic Analytics and manages client engagements.

Lisais an advocate for data science with a prominent role in the New Zealand analytics community, particularly the NZ Statistics Association (NZSA), Operations Research Society of New Zealand (ORSNZ), and the Auckland R-User Group (AKRUG).

Lisa’s views on data science topics are sought widely.  Lisa joined the ‘Q&A with Leading Data Scientists’ panel at the Women in Data Science New Zealand, 2018 event.  She has presented on Big Data topics with NEC at Mobile World Congress in Barcelona in 2014, and on data quality at the GE Digital Summit in Melbourne, July 2016 and Brisbane 2017.

Lisa is a natural teacher and has taught clients how to get the best from R for insightful data analysis and data visualisation.  She has over 10 years’ experience using including designing solution-based models for complex optimisation problems, and analysing large-scale datasets in R.

Lisa has a PhD in Statistics and a Bachelor of Science in Computer Science and Statistics, from the University of Auckland.

Lisa also speaks fluent Mandarin.

Liz MacPherson

Liz MacPherson is a public servant with over 20 years’ experience, including a decade at senior leadership level.

Liz joined the public sector with a strong appetite to make a difference. She is passionate about evidence-driven decision-making. She sees her role is to make sure New Zealand decision-makers at all levels have access to quality information.

Liz was appointed to the role of Government Statistician and Chief Executive of Stats NZ in 2013. She previously held senior roles at the Department of Labour, the Ministry of Economic Development, and the Ministry of Business, Innovation and Employment.

Nasca Peng

Nasca is a statistical analyst and the leader of confidentiality network in Statistics New Zealand. She partners with agencies to promote public trust through official open data and analytical democratisation.

Before joining the New Zealand government, she spent four years working as a consultant for social work agencies, multimillion dollar brands and international start-ups.

Dr Sally (Ake) Nicholas

Ake is a lecturer in linguistics at Massey University. Her research focusses of the description, documentation, and revitalisation of her ancestral language; Cook Islands Māori. As well as linguistic justice more broadly. To that end, she is working on a range of natural linguistic processing oriented projects aimed at accelerating and advancing the description and revitalisation of Cook Islands Māori-  and endangered languages generally. 

Vidette McGregor

Vidette specialises in Fisheries and Ecosystem Modelling, and is Group Manager of the Population Modelling group at NIWA. She has an MSc in Statistics and Operations Research from Victoria University, and is in the final stages of her PhD in Ecosystem Modelling.

Vidette’s work involves researching and applying statistical and mathematical techniques to problems related to the distribution, abundance and dynamics of fisheries and marine populations. This includes single-species models through to full end-to-end ecosystem models, such as Atlantis.