Senior Data Scientist

📋 Description

• • Own the end-to-end lifecycle of data science innovation at Mable, from white-board ideation to production-grade deployment, directly influencing how 25 million+ hours of care are delivered across Australia.
• • Architect and refine machine-learning models that match support workers to clients with sub-second latency, increasing satisfaction scores and reducing time-to-match by double-digit percentages.
• • Pioneer generative-AI solutions—leveraging RAG, agent orchestration and context engineering—to build trustworthy co-pilot tools that empower case managers, carers and families to make faster, safer decisions.
• • Run rigorous A/B and multivariate experiments on new product features, distilling statistical significance into clear narratives that guide executive investment and product road-mapping.
• • Translate terabytes of structured and unstructured data (text chats, reviews, session logs, IoT signals) into actionable insights that unlock new revenue streams and deepen platform trust.
• • Collaborate daily with product managers, ML engineers, UX designers and care-sector experts in agile squads, ensuring every algorithmic improvement is ethical, explainable and aligned to real-world care outcomes.
• • Design and enforce AI-safety guardrails—bias detection, fairness constraints, privacy-preserving techniques—to guarantee compliant, transparent model behaviour in a highly regulated industry.
• • Create self-service dashboards and narrative data stories that democratise insights across 200+ internal users, from C-suite to customer support, cutting ad-hoc query volume by 30%.
• • Champion a culture of reproducible science: version-controlled notebooks, automated CI/CD pipelines, peer code reviews and rigorous documentation that scales knowledge across the growing data org.
• • Mentor junior data scientists and analysts through pair-programming, brown-bag sessions and career-path planning, raising overall team technical bar and retention.
• • Continuously scan the horizon for emerging techniques—probabilistic ML, deep learning, causal inference—and run fortnightly spikes to evaluate business fit before full investment.
• • Contribute to open-source communities and represent Mable at meet-ups, reinforcing our reputation as a bold, switched-on leader in health-tech AI.
• • Balance strategic research with pragmatic delivery in a fast-scaling, two-sided marketplace where priorities can pivot overnight; thrive on ambiguity and maintain a can-do attitude that rallies teams around audacious goals.