Overview
This Data Scientist role offers a unique opportunity to work at the intersection of artificial intelligence, machine learning, and healthcare.
The role will contribute to designing and implementing AI-driven solutions to automate ICD-11 coding from Emergency Department (ED) data, which include structured fields and free text clinical notes.
The appointee will lead the fine-tuning of advanced Large Language Models (LLMs) while ensuring the reliability, accuracy, and compliance of the solution.
Your expertise will help create a pipeline that contributes to reporting of injury related presentations to EDs, predominantly by jurisdictional health departments.
The role will collaborate with clinicians, coders, engineers, and researchers to align solutions with healthcare workflows, working closely with the broader research team partners including CSIRO and AIHW.
There are no direct reports.
The role reports to the Senior Research Fellow and Chief Investigator of this MRFF National Critical Research Infrastructure grant funded work with a dotted reporting line to a Senior Data Scientist at the CSIRO.
Responsibilities
Design and implement AI-driven solutions to automate ICD-11 coding from Emergency Department data (structured fields and free text).
Lead the fine-tuning of advanced Large Language Models (LLMs) and ensure their reliability, accuracy, and compliance.
Collaborate with clinicians, coders, engineers, and researchers to align solutions with healthcare workflows and reporting requirements to EDs.
Work with the broader research team partners including CSIRO and AIHW.
Support data governance, privacy, and regulatory compliance in handling PHI and PII.
Qualifications
PhD or Master's in Data Science, Computer Science, Biostatistics, or related field with relevant experience or equivalent competence gained through education, training and experience.
Fine-tune and validate Large Language Models (LLMs) to assign ICD-11 codes, evaluating performance using metrics such as precision, recall, F1, ROC-AUC, cross-validation.
Demonstrated ability to detect and mitigate bias in AI models and uphold ethical AI standards.
Ensure compliance with privacy regulations (HIPAA, GDPR, local laws) and robust data governance for handling PHI/PII.
Experience with Emergency Department datasets, including structured fields and unstructured free-text data.
Experience developing Data Management Plans, Statistical Analysis Plans, and other project documentation; =2 years in healthcare with knowledge of clinical data and medical vocabulary.
Programming: Python (PyTorch, spaCy), SQL, shell scripting; knowledge of NLP and Transformer architectures.
Excellent written and verbal communication skills to interact with diverse stakeholders and present findings clearly to technical and non-technical audiences.
Desirable Skills
Experience in clinical NLP, especially multi-label classification.
Knowledge of medical terminologies, coding systems (ICD-*****, SNOMED CT).
Knowledge of regulatory requirements for AI/ML in healthcare.
Experience with fine-tuning libraries (e.g., Hugging Face Transformers).
Experience with cloud platforms (AWS, GCP, or Azure).
Pre-employment Checks
Verification of Qualifications
UNSW Benefits And Culture
17% Superannuation and leave loading
Flexible working
Additional 3 days of leave over the Christmas Period
Access to lifelong learning and career development
Progressive HR practices
More information on the great staff benefits and culture can be found here.
How To Apply
Please click on Apply now to apply online.
Applications should not be sent to the contact listed below.
Please provide a resume and a separate document addressing the skills and experience listed in the Position Description.
A copy of the Position Description can be found on JOBS@UNSW.
Interviews are expected to take place mid-January **** due to the UNSW shutdown (Dec 22 – Jan 5).
Contact
Frank McHenry, Talent Acquisition Associate
E:
Applications close: Monday 15th December before *****pm Sydney time
UNSW is committed to equity, diversity and inclusion.
Applications from women, people of culturally and linguistically diverse backgrounds, those living with disabilities, members of the LGBTIQ+ community, and people of Aboriginal and Torres Strait Islander descent are encouraged.
UNSW provides workplace adjustments for people with disability and access to flexible work options for eligible staff.
The University reserves the right not to proceed with any appointment.
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