Manager, Trust Business Intelligence & Insights

Manager, Trust Business Intelligence & Insights

• Full-time

• Workplace Type:
Hybrid

Linked In 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.

At Linked In, 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 Linked In office on select days, as determined by the business needs of the team.

This role will be hybrid in Linked In'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 Linked In’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 Linked In.

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.

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

• Distributed Data Systems

• Python

• Trust & Safety

You will Benefit from our Culture

We strongly believe in the well‑being…