Engineering Director- Ads Measurement

LinkedIn•Mountain View, CA

11h•$231,000 - $378,000•Hybrid

About The Position

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

Requirements

Bachelors degree in a quantitative field - Computer Science, Operational Research, Statistics, Economics or related fields
10+ years of experience in leadership positions

Nice To Haves

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.

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)