Sr. Product Manager - Technical for Lead Qualification , Marketing Technology, AI, and Analytics (TAA)
Posted Updated
Description
AWS Marketing is looking for a Senior Product Manager - Technical to own lead qualification: the machine learning (ML) service that connects Marketing investment to sales outreach. Marketing generates the demand. Your service determines which of that demand is handed off to Sales, starting from the needs of sellers, partners and the Marketing Operations teams who manage the funnel.
ML is at the core of this role. You will evolve a deep-learning propensity model that scores each lead's readiness and likelihood to convert, and own the tooling Marketing Operations uses to see scoring impact, qualify segments and manage exceptions.
You will own lead qualification end to end: deciding how and when leads qualify, setting the thresholds and suppression rules behind those decisions, and keeping qualified leads flowing to Sales based on seller and partner needs. Your focus is delivering qualified leads, making scoring more accurate and transparent, and finding new qualification opportunities in existing demand.
Scope and Impact
ML qualification is how AWS Marketing produces Marketing Qualified Leads (MQLs) at global scale, so a change to the model, its thresholds or the flow of leads reaches every seller and partner who receives them. Small improvements compound across the funnel, which gives this role considerable scope and complexity. Every lead surfaced that would otherwise be missed is return on Marketing investment already made.
Key job responsibilities
- Own the lead qualification roadmap and priorities, including new opportunities to qualify leads from existing demand using customer engagement signals, and make sound trade-offs when data is incomplete.
- Define how and when leads qualify, and set the propensity-score thresholds and suppression rules that determine which leads advance to Sales.
- Drive new iterations of the scoring model with Data Science and engineering teams: translate business problems into model requirements, evaluate technical proposals, and run A/B tests before launching changes globally.
- Own the tooling and exception process Marketing Operations uses to qualify segments and handle cases the model does not.
- Keep qualified leads flowing to sellers and partners, define leading indicators that surface delivery or scoring regressions early, and lead full-funnel diagnosis when conversion or delivery changes.
- Influence without authority across Sales, Marketing Operations and Data Science, bringing stakeholders along from hypothesis through test to scale.
- Represent internal customers by generalizing requirements across sellers, partners and Marketing Operations, and staying close to how qualified leads perform in the field.
- Write the narratives, such as press release and FAQ documents and business cases, that align senior leaders on qualification decisions.
ML is at the core of this role. You will evolve a deep-learning propensity model that scores each lead's readiness and likelihood to convert, and own the tooling Marketing Operations uses to see scoring impact, qualify segments and manage exceptions.
You will own lead qualification end to end: deciding how and when leads qualify, setting the thresholds and suppression rules behind those decisions, and keeping qualified leads flowing to Sales based on seller and partner needs. Your focus is delivering qualified leads, making scoring more accurate and transparent, and finding new qualification opportunities in existing demand.
Scope and Impact
ML qualification is how AWS Marketing produces Marketing Qualified Leads (MQLs) at global scale, so a change to the model, its thresholds or the flow of leads reaches every seller and partner who receives them. Small improvements compound across the funnel, which gives this role considerable scope and complexity. Every lead surfaced that would otherwise be missed is return on Marketing investment already made.
Key job responsibilities
- Own the lead qualification roadmap and priorities, including new opportunities to qualify leads from existing demand using customer engagement signals, and make sound trade-offs when data is incomplete.
- Define how and when leads qualify, and set the propensity-score thresholds and suppression rules that determine which leads advance to Sales.
- Drive new iterations of the scoring model with Data Science and engineering teams: translate business problems into model requirements, evaluate technical proposals, and run A/B tests before launching changes globally.
- Own the tooling and exception process Marketing Operations uses to qualify segments and handle cases the model does not.
- Keep qualified leads flowing to sellers and partners, define leading indicators that surface delivery or scoring regressions early, and lead full-funnel diagnosis when conversion or delivery changes.
- Influence without authority across Sales, Marketing Operations and Data Science, bringing stakeholders along from hypothesis through test to scale.
- Represent internal customers by generalizing requirements across sellers, partners and Marketing Operations, and staying close to how qualified leads perform in the field.
- Write the narratives, such as press release and FAQ documents and business cases, that align senior leaders on qualification decisions.