Chamal Gomes

Summary

Passionate about leveraging data-driven insights to revolutionize the healthcare industry, I am a seasoned Data Science Lead with a proven track record of driving strategic initiatives and delivering impactful solutions. With a blend of technical expertise and leadership skills, I thrive in collaborative environments where I can spearhead innovative projects and mentor teams to success.

💼 Experience

Healthscope - Data Science Lead

2022 Jan - Present

Strategic Insight Development: Formulated and implemented strategies and best practices to enhance the team’s understanding of business needs and challenges, delivering actionable insights that drive significant business value.
Cross-functional Collaboration: Partnered with internal teams and key stakeholders to thoroughly understand and address diverse healthcare domain challenges, proposing and executing effective, data-driven solutions.
Technical Leadership: Lead a high-performing data science team, ensuring the successful execution of impactful projects within budget and time constraints, while maintaining high standards of quality and efficiency.
Innovation for Healthcare Operations: Identification and implementation of bespoke solutions for optimizing healthcare operations with predictive analytics, process automation and Machine Learning. Notable projects include:
- Automated Staff Rostering 21/22 🔗: Developed a 10-week and 72-hour forecast model for optimized and automated staff scheduling across 160+ hospital wards.
- Automated Finance Forecast 22/23: Created an episodic revenue model to enhance finance forecasting and ensure SOX-compliant journal posting.
- Revenue/Coding Optimisation via LLMs 22/23: Utilized large language models (LLMs) to analyze patient medical records for improving patient care and optimizing revenue cycle management process.
ML Ops Architect: Designed and implemented high-performance Azure ML pipeline architectures for efficient ML Ops, Azure Dev Ops, incorporating GitHub CI/CD for streamlined integration and deployment processes.
Mentorship and Training: Mentored junior data scientists and analysts, providing expert guidance on best practices in data science, machine learning, and analytics. Developed and led comprehensive training sessions to enhance team capabilities and foster continuous professional growth.
Cloud Data Warehouse Migration: Designed and developed DBT models in Snowflake as part of a strategic cloud data warehouse migration project. Key models supported critical functions such as patient revenue automation, patient case-mix management, and admission-to-cash flow management.

Tech-stack: LLMOps, Snowflake, Full-stack MLOps, DBT, Python, OpenAI, Git CI/CD, Azure ML DevOps

Healthscope - Data Analyst

2020 Jan - 2021 Dec

Systems Integration: Integration of core clinical and non-clinical hospital source application systems to establish a robust on-premises data warehouse, ensuring seamless data consolidation and accessibility.
Financial Modeling: Development of financial projection models utilised to identify market share by case-mix acuity and demography.
Advanced Predictive Analytics: Applied survival modeling techniques to analyze the probability distribution of hospital-acquired complications and patient readmissions, providing critical insights for risk management.
Machine Learning for Healthcare Operations: Designed revenue and clinical cost decomposition models accounting for inflation and case-mix changes, facilitating benchmarking of best practices across the hospital portfolio.
Operational Dashboards: Developed and maintained a comprehensive suite of operational healthcare dashboards, fostering a culture of evidence-based decision-making and driving operational improvements across hospitals.

Tech-stack: On-Prem Datawarehouse, DAX, PowerBI, SSAS, SAS, Tabular Modelling, M-SQL, VBA, MQuery

NMG Consulting - Actuarial Intern/ Modeling Analyst

2018 Nov - 2019 Apr

Regulatory Reporting and Benchmarking: Managed Regulatory Risk-Based Capital (RBC) submissions for clients, contributing to the benchmarking of industry RBC data to ensure compliance and enhance strategic decision-making
Machine Learning in Fraud Detection: Collaborated with the Prediction Consulting team on a research initiative to apply machine learning methods for fraud detection, focusing on model design and performance evaluation
Comprehensive Reporting: Authored detailed reports documenting the functionality, advantages, and limitations of various machine learning models in the context of fraud detection, providing actionable insights for stakeholders.

💻 Key Skills

Languages

Python, VBA, DAX
ProcSQL, SnowSQL
Bash

ML Stack

Azure MLOps Full-Stack, LLM Ops
Docker, CICD
Azure ML DevOps, Document Intelligence
Batch/Online endpoint deployment

Datawarehouse/Dashboards

DBT, Snowflake, MicrosoftSQL
SSAS Tabular Models, SAS
PowerBI Pro, PowerBI On-Prem

Data Science Stack

LLM Modelling, Time-Series Forecasting
Causal Factor Analysis, Sentiment Analysis
Churn Modelling, Unsupervised Learning
Scenario Modelling, Drift Analysis

🎓 Education

Bachelor of Commerce (Actuarial Science)

University of Melbourne, 2015 - 2017

Master of Commerce (Actuarial Science)(Research Pathway)

University of Melbourne, 2018 - 2019

Awards and Scholarships

University of Melbourne USA Travel Scholarship (San Francisco)
University of Melbourne Commerce Global Scholarship

📜 Research/Publications

Publication Statistics

Total Citations: 64 Google Scholar

Masters Thesis

2018 Jun - 2019 June

Insurance Fraud Detection with Unsupervised Deep Learning. Introduced a novel methodology for fraud detection and experience analysis using unsupervised deep learning models in collaboration with Centre for Actuarial Science at University of Melbourne and University of Hong-Kong.

Publications

2021

Gomes C, Jin Z, Yang H. Insurance fraud detection with unsupervised deep learning. Journal of Risk and Insurance. 2021 Sep;88(3):591-624, https://onlinelibrary.wiley.com/doi/10.1111/jori.12359

👥 Volunteer

University of Melbourne - Mentor

2023 Apr - Present

Providing mentorship for students within the faculty of business and economics with academic pathway guidance, career preparation, and sharing of experience to achieve their set goals and challenges.
🔗 View Program Information

Australian Catholic University - Tutor

2021 Jun - Present

Tutor at the ACU Clemente program for students with disadvantaged backgrounds.
Guiding students with weekly lectures, assignments, and reading material.
🔗 View Program Information