Senior Data Scientist, Trust
Location: Australia | Remote., Melbourne, VIC, Sydney, NSW, Australia
Department: Engineering
Location Type: HYBRID
Employment Type: FULL_TIME
The Role
What You’ll Own
- Define and operationalize the core Trust metric frameworks that anchors company-wide north star goals and cross-functional team performance
- Refine and validate the scoring model used to assess Linktree quality and risk, ensuring heuristic logic is measurable, calibrated, and aligned with policy standards
- Build and maintain production-grade datasets and dashboards that provide reliable visibility into platform risk and system performance
- Identify and size emerging abuse patterns through deep-dive analysis, and translate findings into clear product, policy, operations and engineering priorities
- Partner with Engineering to define evaluation frameworks for ML detection and LLM-based safety systems, including ground truth design and performance benchmarking
- Monitor model health in production (e.g., precision, recall, calibration, drift) and proactively surface degradation, bias, or failure model
- Support Trust incident response through rapid analysis, impact sizing, and postmortem insights that drive durable improvements
- Communicate risk trends and model performance insights through clear visualizations and executive-ready narratives
What You'll Bring
- 5+ years as a Data Scientist in a product-driven technology company
- Direct experience in Trust & Safety, Integrity, Fraud, Security, or other risk-focused domains
- Proven ability to define and operationalize metric frameworks (e.g., Prevalence, Recall, and False Positive Rates) to evaluate the effectiveness of product, policy, or ML-driven interventions
- Experience evaluating machine learning models, including offline methodology, performance tradeoffs (precision/recall, calibration), and production monitoring
- Advanced SQL proficiency and fluency in Python (or R) for advanced analytics and modeling
- Strong foundation in statistics, experimentation design, and causal inference
- Experience working within mature data platforms and analytics engineering stacks (e.g., DBT, Dagster, Airflow)
- Experience designing intuitive, decision-oriented dashboards and compelling data visualizations using tools such as Hex, Looker, Tableau, or PowerBI
- Excellent communication skills with the ability to translate complex statistical findings and risk tradeoffs into clear recommendations for cross-functional stakeholders
- Bachelor’s Degree in a quantitative field (Mathematics, Statistics, Computer Science, Physics, Economics, or related); an advanced degree (MS/PhD) is a strong plus.
Our Story
Where and How We Work
How we’ll help you thrive
- An annual wellbeing allowance to use on things like (but not limited to) fitness memberships, development courses, childcare, travel, charitable donations, pet insurance, home office set-up - the choice is yours!
- 100% coverage (and 80% for your dependents) of your monthly premiums for medical, dental, vision, disability and life insurance for US-based employees.
- Employer contribution towards your retirement.
- Generous time off for vacation, holidays, parental leave, volunteer time, and other categories.
- Employee stock option program - we want each and every employee to share in the company’s success.
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