Senior Data Scientist, Trust

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

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.

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.