The New South Wales Branch of the Statistical Society of Australia warmly invites all undergraduate, postgraduate, and early career statisticians and data scientists to attend our annual Early Career and Student Statisticians event on Tuesday, 13 October 2026, from 6:00pm – 8:00pm, in The Mezzanine at The Loft on Broadway, University of Technology Sydney.
This year, we are delighted to host an inspiring line-up of early and mid-career speakers, spanning academia, government, and industry. They will share what they have learned, achieved, and enjoyed in their careers, as well as the challenges, surprises, and insights that have shaped their journeys.
Each speaker will give a short 5-minute talk with time allotted for questions, followed by a networking session with catering and drinks provided. This is a unique opportunity to connect with peers and professionals in a relaxed setting.
Date: Tuesday 13 October 2026
Time: 6:00pm - 8:00pm AEDT
Venue: The Mezzanine at The Loft on Broadway, University of Technology Sydney
Format: In person
Fees:
- Free for SSA members
- $25 for non-members
Reminder: non-member full-time students can join the SSA for $25 per year, which allows free entry to this event. Click here for more information.
Meet our Speakers
Rory Chen – Project Officer, Centre for Healthy Brain Aging UNSW Sydney
Rory Chen is a health data scientist specialising in the data infrastructure that underpins dementia research. She leads CHeBA’s Dementias Platform Australia (DPAU) initiative, which is dedicated to advancing the FAIR principles - making research data more Findable, Accessible, Interoperable, and Reusable. Her work sits at the nexus of data management, statistical analysis, and the design of scalable, reproducible data workflows. Proficient in R, Python, SAS, SQL, and REDCap, and experienced in cloud computing with AWS, Rory brings strong technical expertise to every stage of the research data lifecycle. She leads the DPAU team using agile project management methodologies and contributes to the broader data science community through active roles in R-Ladies Sydney and the UNSW CodeRs Committee. With more than nine years’ experience working with large, complex datasets, her career spans academic and public health settings. Her previous roles include the National Drug and Alcohol Research Centre (NDARC), UNSW, and the Chinese Center for Disease Control and Prevention (CDC).
Giles Dickenson-Jones – Applied Economist and Public Policy Advisor, Independent Consultant
Giles is an applied economist and public policy advisor working at the intersection of economics, data science and public policy. He began as an economist at the Federal Department of the Treasury during the 2008 Global Financial Crisis before taking research and advisory roles with the Institute for Economics and Peace, the Myanmar parliament and the London School of Economics's International Growth Centre. He now consults independently. Recent work includes advising the Asian Development Bank on an AI-driven job-matching tool for India, designing composite risk indices for the UNDP and building automated policy analysis pipelines for parliaments in the Pacific.
Jie Kang - Applied Statistician, The University of Sydney | CTO, SureStock
Jie Kang is a statistician, researcher and technology leader working at the intersection of statistics, data science and real-world decision making. He is an Applied Statistician at the University of Sydney and Chief Technology Officer of SureStock, an agtech startup developing data-driven tools for livestock health and production. His career has taken him across academia, industry and entrepreneurship, applying statistics to problems ranging from genetics and biomarkers to animal health.
Sarah Lee – PhD Student in Bayesian Statistics, University of Technology Sydney
Sarah Lee is a PhD student in Bayesian Statistics at the University of Technology Sydney. After completing a Bachelor of Commerce, she spent two years working in technology at EY. Wanting to continue learning, she returned to university to pursue research in statistics, with her PhD focusing on Bayesian statistical methods and their applications.
Ika Yuni Wulansari - Statistician, Statistics Indonesia (BPS) | Assistant Professor, Politeknik Statistika STIS | PhD Candidate, University of Technology Sydney | Data Scientist, Health+Law Australia
Ika Yuni Wulansari is a statistician, researcher and educator working across government statistics, academia, data science and applied research. She holds bachelor’s and master’s degrees in Statistics and is currently completing her PhD in Statistics at the University of Technology Sydney (UTS), while maintaining professional roles with Statistics Indonesia (BPS) and Politeknik Statistika STIS. Her research focuses on Small Area Estimation (SAE) and Official Statistics, developing methods that turn complex national data into reliable local evidence for policy and public decision-making. She also contributes to SAE knowledge sharing and collaboration across Australia, New Zealand, and the Pacific region, with research connections extending to Canada and Europe. At Health+Law Australia, Ika works as a data scientist in the quantitative team on the Legal Needs Study (LeNS), working across the survey data workflow from raw data preparation, cleaning and management through to statistical analysis, while supporting interpretation and national- and state-level reporting on the legal needs of people living with HIV and Hepatitis B in Australia. Across these roles, she is driven by rigorous statistical methods to make underrepresented communities more visible in data and to strengthen the evidence available to support better policy, services and decision-making.
Cancellation Policy:
Cancellations received prior to two weeks before the event will be refunded, minus the Stripe processing fee (1.75% + $0.30 per transaction) and an SSA administration fee of $20.
From then on, no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to events@statsoc.org.au.
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