Principal Product Manager

San Francisco, California. Posted 3 months ago

The role

The Principal Product Manager will own large portions of the company roadmap and lead complex product experiences from concept to execution. This individual contributor role involves writing specs, working with customers, and collaborating with engineering, data science, and design to ship AI-driven and data-heavy products.

What you will do

Own big portions of the company roadmap
Lead large, complex experiences from concept to execution
Work directly with customers through calls, onsites, and betas
Drive AI into the core of the product
Partner deeply with Design
Own product quality for launches and run user acceptance testing
Run rigorous product development sprints
Equip go-to-market teams for launches
Collaborate across the company with Engineering, Data Science, Sales, and Customer Success

Required qualifications

7+ years in product management at a B2B SaaS company
Fluency in marketing measurement including MTA, MMM, incrementality testing, pixel and server-side tracking, platform APIs, and privacy constraints
Track record on data-heavy products built on large-scale data pipelines, analytics, or ML models
Demonstrated experience building with AI
Expert in the craft of product including writing specs and PRDs
First-principles problem solver
Customer obsession
Experience partnering closely with design
BS degree required

Nice to have

Engineering, computer science, or data science background
Experience at an analytics company
Experience working in or selling to ecommerce / DTC and performance marketing teams

Benefits

Equity package
Comprehensive healthcare benefits (medical, dental, and vision)
401(k) plan
Flexible PTO policy
12 company-paid holidays
12 weeks of paid parental leave
$500 work-from-home stipend

Before you apply

The interview process typically includes 5-7 interviews totaling 5-8 hours

About the company

Northbeam is building a marketing intelligence platform providing eCommerce brands a unified view of business data through attribution modeling and customizable dashboards. The company uses machine learning and AI to help brands operationalize data and automate decisions.