Senior Principal Product Manager, Advertiser Intelligence (Diagnostics & Keywords)

Microsoft

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Mountain View, CARedmond, WANew York, NY
Salary
$119,800–$234,700 / yr
Posted
14 days ago
Freshness
Confirmed live yesterday
Closes
Mar 9, 2027

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $200k
This role $177k
$106k most similar roles pay here $248k

This role pays less than 67% of similar roles. Most pay $176,212–$224,050 — the shaded band above. At the midpoint, this role pays about $177k versus about $200k for comparable roles.

Based on 240 similar postings.

Employer

About Microsoft

Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing

Microsoft currently has 644 open roles on FindRole.

Listed pay typically runs $119,800–$234,700 across 624 roles with salary data.

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At a glance

TL;DR · Senior Principal Product Manager, Advertiser Intelligence (Diagnostics & Keywords)

Senior/Principal Product Manager-Advertiser Intelligence (Diagnostics & Keywords) joins the Microsoft Advertising team to shape next-generation advertiser intelligence experiences. The role focuses on two distinct areas: Diagnostics or Keyword Intelligence. In the Diagnostics track, the manager transforms static reporting into intelligent, action-oriented workflows using heuristic rules and agentic, AI-powered systems to resolve performance issues. In the Keywords track, the manager leads keyword recommendations and planning by combining large-scale search intent signals with AI-driven insights to identify growth opportunities. Key responsibilities include defining product roadmaps, managing success metrics, and leading cross-functional teams across engineering, design, and data science. The role requires expertise in digital advertising products, including optimization, targeting, and bidding. Candidates must possess skills in building LLM-powered or agentic experiences, utilizing SQL/KQL for data analysis, and executing go-to-market strategies to improve advertiser trust and platform performance.

What does a Product Manager earn in California?

Median $221750 from 153 postings across 39 companies.

See salary data

What you'll do

  • Develop and communicate the product strategy and roadmap for diagnostics or keyword intelligence across the advertising ecosystem.
  • Determine whether to use heuristic rules, agentic workflows, or model-driven approaches to solve specific advertiser problems.
  • Define how products surface across the user journey to maximize engagement and action through instrumentation and experimentation.
  • Analyze campaign data to identify root causes of performance issues and define critical signals for automated troubleshooting.
  • Identify new monetization opportunities by applying AI to large-scale search intent signals and keyword scenarios.
  • Lead go-to-market efforts with marketing and sales teams to ensure successful product launches and adoption.
  • Drive cross-functional alignment between engineering, design, data science, and legal teams to deliver cohesive outcomes.
  • Translate complex data findings into actionable product decisions while ensuring all AI features remain accurate and explainable.

What we're looking for

  • Bachelor's Degree and 5+ years of experience in product, service, or program management.
  • Experience developing digital advertising products, specifically demand/buying side features like optimization, targeting, bidding, budget, and conversion tracking.
  • 8+ years of experience in product, service, or program management (preferred).
  • 3+ years of experience taking a product, feature, or experience to market (preferred).
  • 5+ years of experience improving product metrics such as adoption, engagement, retention, or business impact (preferred).
  • Strong analytical skills and ability to work with data to form hypotheses and translate findings into decisions (SQL/KQL preferred).
  • Experience building AI-powered or agentic experiences including LLMs, agent frameworks, or recommendation systems (preferred).
  • Experience using customer insights and experimentation while collaborating across Design, Engineering, and Data Science (preferred).

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