Engineering Director- Ads Measurement

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 Marketing Solutions (LMS) is the largest and fastest growing B2B Advertising Platform at scale in the world with revenue north of $6B. We help organizations grow.  The LMS engineering team is responsible for building and scaling the technology stack that powers our advertising business including advertiser experiences ad serving platform and ad products. 

Lead product measurement for LinkedIn Marketing Solutions (LMS) Ads Measurement owning experimentation incrementality and attribution strategy and execution across ad products. Partner closely with Product Management Engineering Data Science and Privacy to deliver rigorous privacy-first measurement that drives advertiser outcomes and product adoption.

Top Outcomes

• Establish a company-standard experimentation and incrementality framework used across LMS AMO
• Improve decision quality and speed for product launches and iterations (clear guardrails power analysis confidence intervals)
• Deliver resilient attribution signals that align with privacy constraints and drive better decisioning
• Ship measurement features and APIs that increase measurable lift and advertiser trust
• Build and retain a high-performing measurement team with clear operating mechanisms

Responsibilities

• Own end-to-end measurement strategy for LMS AMO: hypothesis development experiment design lift estimation and causal inference
• Define and scale experimentation guardrails: randomized holdouts multi-cell designs geo tests sequential testing and power/sample-size planning
• Lead incrementality measurement across funnel stages (including BOFU) quantifying true lift for conversions leads and revenue outcomes
• Architect privacy-aware attribution approaches (event-level conversions windows view-through policy path-based and data-driven methods) with robust uncertainty estimates
• Partner with PM/Eng to make measurement a product capability: telemetry requirements experiment platforms APIs dashboards and reviewer workflows
• Establish canonical reporting confidence intervals and decision thresholds to reduce ambiguity and prevent p-hacking
• Collaborate with Privacy Legal and Compliance to ensure methods meet regulatory and platform constraints
• Create operating rhythms: weekly measurement reviews pre-mortems/post-mortems and portfolio-level learning agendas
• Mentor and grow measurement scientists and engineers; set clear goals career paths and hiring plans
• Communicate outcomes to executives and customers in clear actionable narratives (what changed by how much and what we will do next)

Qualifications :

Basic Qualifications

Bachelors degree in a quantitative field - Computer Science Operational Research Statistics Economics or related fields

10 years of experience in leadership positions


Preferred Qualifications

Background in AI/ML techniques with applications to the Advertising domain.  Proven experience designing and building scalable reliable infrastructure for marketing technology platforms with emphasis on data pipelines eventing systems and integration across adtech CRM and analytics ecosystems.

A proven track record of delivering end-to-end solutions for high QPS systems working with massive amounts of data.
 

Proven experience designing and building scalable reliable infrastructure for marketing technology platforms with emphasis on data pipelines eventing systems and integration across adtech CRM and analytics ecosystems.

Experience managing teams of 50 individuals and first/second-line managers. Ability to lead by example and inspire the team to perform at a high level and collaborate very well across different teams.

Good understanding of large-scale engineering systems and some or all of big data technologies like Hadoop Spark distributed key-value stores streaming processes recommender systems statistical methods and experimental design.

Highly motivated and able to work with ambiguous fast-changing problem landscapes convert vague and ill-defined problems into well-defined problems take initiative and encourage consensus building across partners.

Strong leadership abilities in order to communicate and drive cross-functional efforts. Good relationship building and people skills.

Publications at conferences and patents are highly desirable.


Suggested Skills:
* People Leadership
* Ads experience
* AI/ML experience


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 alllevels.

LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $231000 to $378000. 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 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 and describe the specific Accommodation requested for a disability-related limitation.
Fill out an Accommodation request here: 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 LinkedIns 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: Data Privacy Notice and Compliance Posters for Job Candidates 

Please use this link to access documents that provide information about how LinkedIn handles the personal data of employees and job applicants as well as the E-Verify Participation Notice and the Department of Justice Immigrant and Employee Rights Section Right to Work posters: Work :

No

Employment Type :

Full-time