
Data Strategist
2 weeks ago
We empower better healthcare decisions by uncovering meaning from large-scale health data sets and delivering powerful, data-driven strategies.
Leverage advanced data analytics, predictive modeling, and real-world data to deliver high-impact outcomes for pharmaceutical companies, healthcare providers, and governments across Australia and globally.
- 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.
- 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 expertise: advanced SQL (joins, windows, aggregations); Python (NumPy, pandas, scikit-learn, XGBoost); data visualization 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.
The successful candidate will be part of a dynamic team that empowers better healthcare decisions through data-driven strategies. We offer a collaborative and innovative work environment that fosters growth and development.
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