Sr. Product Manager, Specialized Modeling & Verticals

6sense

8d•$144,506 - $211,943•Remote

About The Position

At 6sense, our core predictive foundation provides the engine, but our specialized models provide the steering for specific business outcomes. We are looking for a Sr Product Manager to own Specialized Modeling & Verticals—focusing on the intelligence that powers verticalized tasks and addresses specific B2B marketing needs. You will work closely with the PM Lead to leverage foundational intelligence and build out specialized layers that solve the specialized enterprise revenue challenges.

Requirements

Applied ML Expertise. You have experience managing ML products and are comfortable discussing model inputs, logic, and validation with data scientists.
B2B Domain Knowledge. You understand the B2B revenue lifecycle—leads, accounts, opportunities, and the complex challenges that come with them.
Strategic Partnering. A proven ability to work with other PMs. You know how to leverage foundational platforms to build specialized value.
Execution Rigor. You excel at taking a high-level capability and turning it into a specific, shipped feature that solves a concrete user pain point.
4-6+ years in Product Management, with a focus on Data Products, AI/ML, or B2B SaaS applications.

Responsibilities

Drive Specialized Modeling Initiatives. Lead the roadmap for intelligence layers that address verticalized tasks and specific B2B marketing needs. You ensure that core signals are translated into high-value specialized business outcomes.
Develop Specialized, Use-Case Specific Models. Partner with business stakeholders, customers, and data science teams to build specialized models fed by our core engines, ensuring our intelligence remains highly relevant and accurate across diverse business scenarios.
Own the "Applied Intelligence" Roadmap. Work with the Predictive Lead to consume core engines and turn them into specialized features that solve complex, domain-specific challenges for the world's largest enterprises.
Maximize Model Utility. Ensure that specialized models are built with a "leveraged" mindset—creating solutions that solve a broad class of problems rather than one-off custom requests.
Define Domain-Specific Requirements. Act as the bridge between specialized business workflows (like Sales Ops or Demand Gen) and our data science teams, translating complex business problems into clean modeling requirements.
Measure Impact in Context. Establish performance metrics that aren't just about model accuracy, but about how effectively these specialized signals drive real-world revenue outcomes.