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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.

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.

LinkedIn’s InfoSec Risk Organization is seeking a strategic and technically adept Senior Manager of Risk Data Science to lead a team focused on quantifying, modeling, and mitigating information security risks across the enterprise. This role is pivotal in advancing LinkedIn’s risk posture through data-driven insights, continuous controls assurance, and scalable risk programs aligned with global regulatory frameworks including ISO 27001, NIST CSF, SOX, DMA (Digital Marketing Act), AI Regulations and the Digital Services Act (DSA).

You will collaborate cross-functionally with engineering, legal, compliance, and product teams to embed risk intelligence into operational workflows and strategic planning. This role is ideal for a leader who thrives at the intersection of data science, security, and governance.

Responsibilities:

• Define the strategic vision and roadmap to empower InfoSec by deepening our understanding of governance, controls, risk, and compliance systems, enabling effective optimizations and data-informed decisions.

• Design and implement automated control monitoring systems to continuously validate security control performance and surface emerging vulnerabilities.

• Develop and operationalize machine learning and statistical models to assess threat likelihood, control effectiveness, and systemic risk exposure.

• Lead risk assessment and maturity initiatives, including executive reporting, audit preparedness, and alignment with security, privacy, AI, and resiliency frameworks.

• Build secure data pipelines, dashboards, and analytics platforms that improve visibility into security posture and support risk-informed decision-making.

• Ensure risk analytics, controls assurance, and reporting meet regulatory, compliance, and internal governance requirements.

• Establish prioritization frameworks and partner alignment to ensure security efforts are focused on the highest-impact risks.

• Analyze large-scale structured and unstructured data, generating insights that strengthen control effectiveness, incident prevention, and customer trust.

• Research, develop, and deploy cutting-edge methodologies that improve systemic risk measurement, forecasting, and security program scalability.

• Partner cross-functionally with InfoSec engineering, product security, TPMs, and business stakeholders to embed risk intelligence into engineering and operational workflows.

• Lead the team to deliver strong results by researching and building cutting edge, leverageable methodologies and solutions.

• Be a role model and professional coach for data scientists and managers. Help them realize their potential by setting clear expectations, openly evaluating performance, upholding accountability, and providing challenges (within and outside their team) to stretch their skills.

• Align with relevant teams on prioritization.

• Build strong collaboration and connective tissue with the other Line of Business Data Science teams and with key horizontal DS functions.

• Represent the organization as an industry thought leader in security analytics, resilience, and risk measurement forums.

Basic Qualifications:

• BS or above degrees in a quantitative field - Computer Science, Operational Research, Statistics, Economics, or related fields

• 7+ years of relevant industry or relevant academic experience in Data Science / Analytics working with data; 2+ years experience in managing a team

• Experience with SQL/Relational databases and data visualization tools

• Experience in applied statistics

Preferred Qualifications:

• 10+ years of relevant work experience

• 7+ years of experience in information security, risk management, or GRC.

• 7+ years of hands-on programming experience (e.g., Python, SQL, Java, Scala).

• Experience with large-scale distributed systems and cloud infrastructure (AWS, Azure, GCP).

• 5+ years of experience managing technical teams.

• 2+ years of experience applying ML/AI to risk modeling or threat detection.

• Proven ability to design and implement continuous controls assurance frameworks.

• MS/PhD degree in a quantitative or cyber security-related discipline (i.e. Computer Science, Operational Research, Statistics, Economics)

• Strong leadership with track records in building high performing Data Science teams, driving projects, applying strategic thinking, building thought leadership and influencing senior leaders and executives

• Experience designing and deploying secure, scalable web applications or internal platforms.

• Excellent communications skills, with the ability to synthesize, simplify and explain complex problems to different types of audience, including executives

• Familiarity with identity and access management systems (OAuth, SAML, Zero Trust).

• Deep understanding of standards and regulatory frameworks (SOX, ISO 27001, PCI DSS, NIST, GDPR, EU DSA, EU AI, EU DMA).

• Experience contributing to strategic planning, scorecard development, and portfolio reviews.

• Experience with enterprise AI/ML platforms such as Azure Machine Learning, Azure AI Foundry, or Microsoft Fabric or equivalent.

• Familiarity with model evaluation frameworks (e.g., Gen AI Robustness Analyzer, Responsible AI Toolkit).

• Hands-on experience with data science tools (e.g., Python, SQL, Jupyter, Power BI) and ML lifecycle management.

• Knowledge of AI governance standards (e.g., NIST 800-218a, MITRE Atlas, EU AI Act).

Suggested Skills:

• People Leadership

• InfoSec experience

• Data Science / Analytics

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 $168,000-$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 [email protected] 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.