Data Driven Healthcare Solutions

We are seeking a highly skilled analytics professional to join our team and drive business growth through data-driven insights.

This is a hands-on role where you will leverage advanced data analytics, predictive modeling, and machine learning to deliver high-impact outcomes for pharmaceutical companies, healthcare providers, and governments across Australia and globally.

As a Senior Analytics Consultant, you will support the full lifecycle of pharmaceutical products—from development to market launch and post-market monitoring—using advanced analytics to uncover key trends and opportunities.

• Conduct market sizing, cohort analysis, risk stratification, and KPI modeling to inform product and marketing strategies.
• Build and optimize automated data pipelines (e.g., in Dataiku) to improve reporting efficiency and deliver faster insights.
• Develop and present interactive dashboards, visualizations, and executive presentations to communicate findings to stakeholders.
• Partner with Sales teams to translate analytical insights into scalable, productized solutions that align with our platform vision.
• Collaborate with regional analytics teams, sharing best practices in predictive modeling, machine learning, and advanced SQL querying to ensure consistent quality and innovation.
• Mentor junior team members, promoting analytical excellence and knowledge sharing.

Supporting the full product lifecycle from development to market launch and post-market monitoring using advanced analytics to uncover key trends and opportunities.

Conducting market sizing, cohort analysis, risk stratification, and KPI modeling to inform product and marketing strategies.

Building and optimizing automated data pipelines to improve reporting efficiency and deliver faster insights.

Developing and presenting interactive dashboards, visualizations, and executive presentations to communicate findings to stakeholders.

Partnership with sales teams to translate analytical insights into scalable, productized solutions that align with our platform vision.

Collaboration with regional analytics teams, sharing best practices in predictive modeling, machine learning, and advanced SQL querying to ensure consistent quality and innovation.

Mentoring junior team members, promoting analytical excellence and knowledge sharing.

• 5+ years’ experience working with pharma clients, leveraging longitudinal real-world patient datasets to solve use cases such as forecasting, brand performance tracking, prescriber targeting, segmentation, patient journeys, and omni-channel attribution.
• Strong solutioning mindset: able to engage directly with clients, unpack requirements through probing Q&A, translate business needs into analytical designs, and own the problem→solution path.
• Proven client communication skills: confident running pharma stakeholder meetings, handling back-and-forth to refine scope, and presenting insights.
• Team leadership: experience managing and mentoring analysts/scientists; setting standards, reviewing work, and building repeatable best practices.
• Technical excellence: advanced SQL (joins, windows, aggregations); Python (NumPy, pandas, scikit-learn, XGBoost); data viz in Power BI; power-user of Excel (VBA/Macros, Power Query). Able to take a brief and query/shape data end-to-end independently.
• Healthcare analytics background with real-world/claims/EMR data; comfortable with clinical context (e.g., indications, lines of therapy, persistence, switching) and quick to learn unfamiliar disease areas.
• Degree in a quantitative field (Engineering, Mathematics, Statistics, Computer Science, Health Economics) or equivalent experience.
• Mindset: hungry, curious, and proactive - eager to learn and continuously raise the bar for the team.

• Impact: Work on projects that improve healthcare delivery and patient outcomes globally.
• Growth: Be part of a rapidly scaling company with career advancement opportunities.
• Culture: Join a collaborative, mission-driven team passionate about healthcare and data.
• Learning: Access professional development, mentorship, and exposure to advanced analytics technologies.