Lead Data Scientist

Lead Data Scientist

Turn rich health data into AI that changes lives

At Resmed, we use AI and machine learning to improve the lives of people living with sleep and respiratory conditions. Working with one of the world's richest physiological, clinical, and digital health datasets, you'll help solve complex healthcare challenges that impact millions of patients globally.

As Lead Data Scientist, you'll provide technical leadership across high-impact AI initiatives, taking problems from raw physiological signals through to clinically validated, production-ready models. You'll work closely with Engineering, Product, Medical Affairs, and Regulatory teams to deliver AI solutions that are scientifically rigorous, clinically meaningful, and globally scalable. You'll also play a key role in mentoring fellow data scientists and elevating the team's technical standards.

What You'll Do

Lead the end-to-end design, development, validation, and deployment of machine learning models using physiological and digital health data.

Translate clinical and product challenges into robust machine learning solutions with appropriate labels, metrics, and validation approaches.

Apply digital signal processing and modern machine learning techniques to wearable and medical device data.

Establish modelling standards and provide technical leadership on time-series and biomedical signal problems.

Develop rigorous evaluation frameworks that account for clinical ground truth, class imbalance, and patient-level generalisation.

Partner with Data Engineering and Platform teams to productionise models and build scalable pipelines.

Collaborate with Medical Affairs, Clinical, Regulatory, and Quality teams within a regulated healthcare environment.

Mentor data scientists through technical reviews, coaching, and best practice sharing.

Communicate complex scientific concepts clearly and influence decisions through evidence-based reasoning.

What You'll Bring

Master's degree or PhD in Data Science, Computer Science, Electrical Engineering, Biomedical Engineering, Statistics, Applied Mathematics, Physics, or a related quantitative field.

Significant industry experience applying machine learning to real-world problems and leading projects end-to-end.

Deep expertise across machine learning approaches, including classical methods, ensemble models, and deep learning techniques.

Strong experience working with time-series data and signal processing techniques.

Solid foundation in statistics, experimental design, and model validation.

Advanced Python and SQL skills, with experience developing production-quality code.

Experience working with cloud and data platforms such as AWS and Snowflake.

Proven ability to influence cross-functional stakeholders and lead technical direction.

Nice to have:

Experience working with physiological or wearable signals such as PSG, EEG, ECG, PPG, respiratory flow/pressure, or SpO2.

Background in healthcare, medical devices, or regulated environments.

Familiarity with Software as a Medical Device (SaMD) and AI/ML lifecycle management.

Experience partnering with clinical and medical stakeholders.

What Sets You Apart

Scientific curiosity - Enjoy exploring complex problems and uncovering insights from challenging data.

Technical judgement - Balance innovation with practical decision-making and business impact.

Collaborative leadership - Build trusted partnerships and bring diverse teams together around a common goal.

Ownership mindset - Take accountability for outcomes and move confidently through ambiguity.

Mentorship focus - Invest in the growth of others and help raise the technical bar across the team.

Patient-first thinking - Remain motivated by the opportunity to improve health outcomes at scale.

Why Join Resmed

At Resmed, we create life-changing health technologies that people love. Our AI-powered digital health solutions, cloud-connected devices, and intelligent software help make healthcare more personalised, accessible, and effective for millions of people worldwide. Operating in more than 140 countries, we're combining data, technology, and healthcare expertise to transform how care is delivered in the home.

We are committed to building a diverse and inclusive workplace and welcome applications from people of all backgrounds.