At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. The Trust Data Science team powers the mission of creating safe, trusted, and professional experiences on LinkedIn through rigorous metrics, experimentation, and advanced data solutions. Measuring trust is inherently challenging as abuse is adversarial, ground truth is noisy, and outcomes are often long-tailed. We tackle these challenges using advanced statistical techniques to design and build robust, actionable metrics, make them experimentable, while building highly reliable, semantically rich data pipelines enabling data-driven decision making across the Trust organization. In this role, we are looking for a technical leader in the Anti-abuse domain, specifically focused on mitigating harm from inauthentic accounts (fake accounts and account compromise / take overs) and behavioral abuse (scraping, automation and fake engagement). Accounts and Behavioral anti-abuse is one of the top priorities at Trust and has a foundational impact on the health of LinkedIn's ecosystem through protection of our member's identity and social graph. This person will work closely with various cross-functional teams such as product, engineering, design, AI, legal, and operations in Trust areas, to develop and deliver complex metrics, analyses / inferences, data solutions that inform critical decisions. Successful candidates will exhibit technical acumen, product sense and business savvy, with a passion for making an impact through creative storytelling and timely actions.