Group Product Manager, IAP Advertising Performance

Description

The company builds AI-driven performance advertising. It was founded in 2013 by machine learning engineers who had built AI ad systems at the largest technology companies, and it set out to bring that same engine to the open internet.

It runs two businesses on one core AI system. The ads platform helps mobile app marketers acquire, retain, and re-engage high-value users across the open internet. The commerce media platform lets retailers and marketplaces build ad businesses on their own platforms.

This role sits at the center of the ads platform's largest business, in-app purchase (IAP) advertising. The team works on hard AI advertising problems at a scale few companies reach.

The core challenge: every impression requires real-time decisions about user intent, conversion odds, creative fit, auction economics, budget pacing, and signal quality. Many valuable user, app, and conversion combinations are sparse or never seen before.

The role sets the product direction for the system, decides where to invest, builds a durable multi-year performance roadmap, and makes sure bidding, recommendations, signals, and campaign automation add up to better advertiser results.

Responsibilities

• Set the vision, strategy, and multi-year roadmap for IAP performance across ad recommendations, bidding, signals, and campaign automation.
• Own the product strategy for IAP outcomes on Android and iOS, with a focus on gaming and other high-value app categories.
• Lead the bidding control tower, covering bid optimization, auction strategy, budget allocation, pacing, value optimization, and performance monitoring.
• Turn advances in machine learning, data, and platform infrastructure into features that raise advertiser scale, return on ad spend, cost per acquisition, and downstream user value.
• Define how conversion events, measurement partner data, publisher interactions, SDK activity, and bid requests are collected, evaluated, enriched, and used.
• Work with the UA SDK and signal engineering teams to improve the quality, coverage, and timeliness of signals for IAP models.
• Shape recommendation models that estimate intent, conversion probability, and advertiser value in real time, including sparse-signal and cold-start cases.
• Define how campaign automation helps advertisers pick objectives, set up campaigns, find optimization gains, and act on performance insights.
• Align product choices across optimization objectives and measurement methods, such as event-based optimization, predicted lifetime value, SKAN, value multipliers, and other performance controls.
• Build measurement and experimentation frameworks that separate local model gains from lasting advertiser and business improvements.
• Work with data science, machine learning, and engineering leaders to assess model quality, diagnose gaps, and balance quick wins against structural fixes.
• Keep product, engineering, science, operations, and go-to-market teams aligned on priorities, launch plans, operating routines, and customer feedback.
• Report progress to senior leadership, build support for investment decisions, and hold the team accountable for results.
• Within 90 days, learn IAP performance, the bidding control tower, and the best opportunities on Android and iOS; build working relationships with engineering, machine learning, data science, UA SDK, and go-to-market partners; create a shared view of the backlog, metrics, dependencies, and decision forums; and ship a focused set of near-term gains while defining long-term strategy.
• Over time, make IAP performance work a measurable, ongoing product practice; deliver structural gains through better recommendations, bidding, signal use, and automation; give advertisers a clear way to state business goals that the system optimizes toward; and make every campaign produce better data and every new signal lift the whole system.

Requirements

• 10+ years of experience, including substantial product management in ad tech, machine learning, marketplaces, optimization systems, or another technically complex field.
• A record of owning products end to end, from problem definition and roadmap through execution, launch, and measurable business impact.
• A record of turning complex ML, data, or platform capabilities into customer and business results.
• Strong reasoning about performance systems, experimentation, metrics, and trade-offs when data is noisy, incomplete, or probabilistic.
• Comfort working closely with engineering, machine learning, data science, and infrastructure teams on highly technical products.
• The ability to move between executive strategy and implementation detail without losing sight of the system.
• Sound product judgment and prioritization, with a knack for finding the few bets most likely to produce lasting gains.
• A history of leading cross-functional work across several teams, competing priorities, and a globally distributed organization.
• Clear communication that builds conviction with senior leaders, technical partners, and customer-facing teams.
• Comfort in ambiguous problem spaces, learning fast, forming hypotheses, and refining strategy with evidence.
• A focus on customer outcomes, with the ability to link platform and model investments to advertisers' workflows, goals, and economics.
• Experience with mobile advertising, in-app purchase or app-growth economics, gaming, DSPs, ad exchanges, or real-time bidding.
• Experience building bidding, recommendation, campaign automation, identity, signal, measurement, or optimization products.
• Experience with predicted lifetime value, event-based optimization, SKAN, value-based bidding, or mobile measurement ecosystems.
• Experience leading products that cover both platform capabilities and advertiser-facing workflows.
• Experience with SDK-based products, publisher integrations, or signal collection and quality systems.
• An MBA, or a degree in computer science, statistics, engineering, or another technical or analytical field.

Conditions

The role is based in the location stated in the posting. Base pay depends on region: Region A (Menlo Park Office, New York Office, SF Bay Area, New York Metro Area) is $211,200-$264,000 USD; Region B (Seattle Office, Seattle, Los Angeles/Orange County, San Diego, Austin, Boston, Washington DC Metro Area, Miami) is $190,000-$237,500 USD; Region C (all other U.S. locations) is $179,600-$224,500 USD.

Your region follows your assigned work location.

The company is an equal opportunity employer and does not discriminate on protected characteristics.

Benefits

• U.S.-based employees get medical, dental, and vision insurance, a 401(k) with company match, short-term and long-term disability cover, basic life insurance, and well-being perks.
• U.S.-based employees get up to 12 scheduled paid holidays per calendar year and one Thrive Day off per quarter.
• All employees get Flexible Time Off (FTO).
• The role may be eligible for a bonus and equity awards. Eligibility and amounts depend on performance and the terms of the applicable plans.
• Benefits vary by country, employment type, and eligibility. A recruiter can explain what applies in your region.