Manager, Trust Business Intelligence & Insights

Company Description

LinkedIn is the world’s largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed.

Join us to transform the way the world works.

Job Description

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.

This role will be hybrid in LinkedIn's Mountain View campus.

The Trust Business Intelligence & Insights Manager is a cross-functional leadership role that blends data science, data management, analytics, and strategy to create impact at global scale. You will lead a talented team of analysts while partnering closely with product, trust, engineering, policy, and data science teams. Together, you’ll build models and insights that help keep members and our platform safe.

Responsibilities

Leadership:

Partner with teams in, Product, Engineering, Policy, Finance, and Operations to identify new opportunities, challenge assumptions, and align data-driven goals , driving transformative outcomes across Trust.
Define and execute a multi-year vision for Trust Ops Data initiatives supporting LinkedIn’s trust and operational goals.
Lead and develop high-performing teams of analysts across geographies; mentor senior talent and foster a culture of excellence, inclusion, and craftsmanship.
Collaborate with engineering and data science teams to shape data platform evolution enabling scale.


Technical Execution

Leverage the world’s richest professional dataset to uncover insights that improve member engagement, marketplace integrity, and business growth.
Develop advanced models, causal inference frameworks, and experiments to evaluate new features, trust defenses, and understand impact of efficiencies.
Build and maintain data pipelines, metrics, dashboards, and insights to enable data-driven decisions across LinkedIn.
Lead technical reviews, ensure data and code quality, and define engineering best practices for data systems operating at massive scale.
Translate analytical findings into clear, compelling narratives that influence executive decision-making.
Develop compelling data visualizations and narratives that translate complex data into clear, actionable insights for diverse audiences.


Qualifications

Basic Qualifications

BA/BS in a quantitative discipline (Computer Science, Statistics, Applied Mathematics, Engineering, Operations Research, Economics, etc.) , or related technical discipline, or equivalent practical experience.
10+ years of experience in Data Science, Business Intelligence, or Analyst roles
1+ year(s) of management experience or 1+ year(s) of staff level engineering experience with management training
Experience with SQL and at least one programming language (Python, R, Java)
Experience with large-scale distributed data systems (e.g., Hadoop, Spark, Hive, Presto)
Experience designing and analyzing large data sets and applying statistical modeling techniques


Preferred Qualifications

Master’s or PhD degree in Computer Science, Statistics, Applied Mathematics, Engineering
Excellent communication and storytelling skills with the ability to influence both technical and executive audiences
Experience leading cross-functional data or AI programs in a global technology company
Strong background in applied statistics, causal inference, A/B testing, and machine learning
Experience in Trust & Safety, Anti-Abuse, or Growth domains


Suggested Skills:

Technical Leadership
Business Analytics & Intelligence
Distributed Data Systems
Python
Trust & Safety


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. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $116,000 to $193,000. Actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For additional information, visit: https://careers.linkedin.com/benefits.

Additional Information

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.

San Francisco Fair Chance Ordinance

Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.

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

Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.