Senior Data Scientist, Trust

About the role

As a Senior Data Scientist on Linktree’s Trust team, you will play a key role in protecting the integrity and health of our platform. You will apply your expertise in data science and statistical modeling to define how we measure harm, assess platform risk, and continuously improve our detection and mitigation systems.

Responsibilities

• 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

Requirements

• 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

Qualifications

• Bachelor’s Degree in a quantitative field (Mathematics, Statistics, Computer Science, Physics, Economics, or related); an advanced degree (MS/PhD) is a strong plus

Skills

• Expertise in data science and statistical modeling
• Ability to define and operationalize metric frameworks
• Experience evaluating machine learning models
• Strong foundation in statistics, experimentation design, and causal inference
• Experience working within mature data platforms and analytics engineering stacks
• Experience designing intuitive, decision-oriented dashboards and compelling data visualizations
• Excellent communication skills

Benefits

• An annual wellbeing allowance
• 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
• Employee stock option program

Pay

Final offers depend on multiple factors including location, experience, expertise, and role scope, and may vary from the range listed.

Schedule

We are a global, diverse team spread across continents with offices in London, Los Angeles, Melbourne, and San Francisco. We work together flexibly and you can choose the setup that works best for you: fully remote or a hybrid mix of office and home.