Senior Staff Data Scientist, Trust and Anti-Abuse
Data Science
United States
USD 168k-276k / year + Equity
Posted on Aug 5, 2025
LinkedIn is the world’s largest professional network, built to help members of all backgrounds and experiences achieve more in their careers. Our vision is to create economic opportunity for every member of the global workforce. Every day our members use our products to make connections, discover opportunities, build skills and gain insights. We believe amazing things happen when we work together in an environment where everyone feels a true sense of belonging, and that what matters most in a candidate is having the skills needed to succeed. It inspires us to invest in our talent and support career growth. Join us to challenge yourself with work that matters.
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.
About Trust Data Science at LinkedIn
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.
About Role
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.
Responsibilities
• Partner with cross-functional teams to initiate, lead and drive to completion large-scale/complex strategic projects for teams, departments and the company.
• Act as a thought partner to senior leaders to prioritize/scope projects, provide recommendations, and evangelize data-driven business decisions in support of strategic goals.
• Provide technical guidance and mentorship to junior team members on solution design as well as lead code/design reviews.
• Drive org-wide impact by shaping product and business strategy through data-centric presentations.
• Work with a team of high-performing data science professionals, and cross-functional teams to identify business opportunities, optimize product performance or go to market strategy.
• Analyze large-scale structured and unstructured data; develop deep-dive analysis and machine learning models to drive member value and customer success.
• Design and develop core business metrics, create insightful automated dashboards and data visualization to track them and extract useful business and product insights.
• Design and analyze experiments to measure the impact of new Trust defenses, assess collateral damage on growth metrics, and quantify unintended Trust risks from product or marketplace changes. Translate results into clear, actionable recommendations, and drive alignment through compelling, insight-driven narratives
• Collaborate with engineering to ensure scalable, reliable, and discoverable data infrastructure that powers experimentation and insights
Basic Qualifications
• B.S. Degree in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc.
• 5+ years relevant work experience in anti-abuse / adversarial areas like Fake Accounts and ATOs
• 5+ years experience with SQL and at least one programming language (e.g., R, Python, Scala)
• 2+ years experience in an architect or technical leadership position
Preferred Qualifications
• 10+ years of overall experience with at least 5+ of those years leading teams technically
• Experience influencing strategy through data-centric presentations .
• Experience in applied statistics and statistical modeling in at least one statistical software package.
• Experience telling stories with data and visualization tools
• Experience running platform experiments and techniques like A/B testing
• Ability to work with multiple stakeholders, understand the product priorities, think with the big picture and solve core problems in the most efficient way
• Experience with manipulating massive-scale structured and unstructured data.
• Proven record writing and optimizing code with high levels of craftsmanship, and coaching others to improve technical outputs.
• Working knowledge of Unix command-line/shell, git and review board.
• Experience leveraging government data or publicly available third-party APIs.
• Experience mentoring other data scientists in an official or unofficial capacity.
• Excellent communication skills, with the ability to synthesize, simplify and explain complex problems to different types of audience, including executives and compile compelling narratives.
Suggested Skills:
• Data Science
• Causal inference
• A/B Testing
You will Benefit from our Culture:
We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.
The pay range for this role is $168,000 to $276,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor.
The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits
Equal Opportunity Statement
We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.
If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at accommodations@linkedin.com and describe the specific accommodation requested for a disability-related limitation.
Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:
-Documents in alternate formats or read aloud to you
-Having interviews in an accessible location
-Being accompanied by a service dog
-Having a sign language interpreter present for the interview
A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.
LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.
Pay Transparency Policy Statement
As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.
Global Data Privacy Notice for Job Candidates
This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://lnkd.in/GlobalDataPrivacyNotice
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.
About Trust Data Science at LinkedIn
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.
About Role
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.
Responsibilities
• Partner with cross-functional teams to initiate, lead and drive to completion large-scale/complex strategic projects for teams, departments and the company.
• Act as a thought partner to senior leaders to prioritize/scope projects, provide recommendations, and evangelize data-driven business decisions in support of strategic goals.
• Provide technical guidance and mentorship to junior team members on solution design as well as lead code/design reviews.
• Drive org-wide impact by shaping product and business strategy through data-centric presentations.
• Work with a team of high-performing data science professionals, and cross-functional teams to identify business opportunities, optimize product performance or go to market strategy.
• Analyze large-scale structured and unstructured data; develop deep-dive analysis and machine learning models to drive member value and customer success.
• Design and develop core business metrics, create insightful automated dashboards and data visualization to track them and extract useful business and product insights.
• Design and analyze experiments to measure the impact of new Trust defenses, assess collateral damage on growth metrics, and quantify unintended Trust risks from product or marketplace changes. Translate results into clear, actionable recommendations, and drive alignment through compelling, insight-driven narratives
• Collaborate with engineering to ensure scalable, reliable, and discoverable data infrastructure that powers experimentation and insights
Basic Qualifications
• B.S. Degree in a quantitative discipline: Statistics, Operations Research, Computer Science, Informatics, Engineering, Applied Mathematics, Economics, etc.
• 5+ years relevant work experience in anti-abuse / adversarial areas like Fake Accounts and ATOs
• 5+ years experience with SQL and at least one programming language (e.g., R, Python, Scala)
• 2+ years experience in an architect or technical leadership position
Preferred Qualifications
• 10+ years of overall experience with at least 5+ of those years leading teams technically
• Experience influencing strategy through data-centric presentations .
• Experience in applied statistics and statistical modeling in at least one statistical software package.
• Experience telling stories with data and visualization tools
• Experience running platform experiments and techniques like A/B testing
• Ability to work with multiple stakeholders, understand the product priorities, think with the big picture and solve core problems in the most efficient way
• Experience with manipulating massive-scale structured and unstructured data.
• Proven record writing and optimizing code with high levels of craftsmanship, and coaching others to improve technical outputs.
• Working knowledge of Unix command-line/shell, git and review board.
• Experience leveraging government data or publicly available third-party APIs.
• Experience mentoring other data scientists in an official or unofficial capacity.
• Excellent communication skills, with the ability to synthesize, simplify and explain complex problems to different types of audience, including executives and compile compelling narratives.
Suggested Skills:
• Data Science
• Causal inference
• A/B Testing
You will Benefit from our Culture:
We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.
The pay range for this role is $168,000 to $276,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor.
The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits
Equal Opportunity Statement
We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.
If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at accommodations@linkedin.com and describe the specific accommodation requested for a disability-related limitation.
Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:
-Documents in alternate formats or read aloud to you
-Having interviews in an accessible location
-Being accompanied by a service dog
-Having a sign language interpreter present for the interview
A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.
LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.
Pay Transparency Policy Statement
As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.
Global Data Privacy Notice for Job Candidates
This document provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://lnkd.in/GlobalDataPrivacyNotice