Sr Product Manager, Product Usage

NRG•VIRTUAL, WA

2d•$155,000 - $190,000

About The Position

Welcome to the intersection of energy and home services. At NRG, we’re driven by our passion to create a smarter, cleaner and more connected future. Vivint Smart Home, an NRG owned company, is a leading smart home company in the United States, dedicated to redefining the home experience with intelligent products and services. We find purpose in proactively protecting and keeping our customers connected to home, no matter where they are. Join the Smart Home team to create smarter, safer and more sustainable homes. The Senior Manager of Product Usage & Insights will act as a single-threaded business and data owner responsible for analyzing how customers interact with the Vivint smart home ecosystem. This role focuses on translating post-launch device telemetry, customer support data, and operational metrics into actionable insights. You will bridge the gap between real-world product performance and future state design, serving as a critical insights engine for core Product Managers. In this role, you will dive deep into device usage patterns, troubleshooting calls, and product issues to identify functional gaps and roadmap opportunities. You will operate cross-functionally to aggregate data across the business, while also spearheading the development of internal AI and data tools to help team members more efficiently understand customer behavior and business trends. Your ultimate mission is to ensure our product teams have the deep data required to evolve features, optimize hardware, and deliver a seamless customer experience.

Requirements

Exceptional proficiency in data manipulation and statistical analysis.
Baseline skills in SQL, data visualization platforms (e.g., Tableau, PowerBI), and Excel are required.
Strong diagnostic instincts with the ability to look past surface-level symptoms in customer support logs to identify underlying firmware, hardware, or software flaws.
Proven ability to build strong working relationships and align priorities across diverse corporate functions without relying on direct authority.
Solid understanding of how to apply basic data science workflows or leverage low-code/no-code internal AI frameworks to automate business intelligence.
4–6+ years of experience in product analytics, business intelligence, operations framework management, or a data-focused product management role.
Direct experience working within consumer electronics, IoT, telecommunications, or subscription-based software services is highly preferred.
Demonstrated success aggregating data from operations, supply chain, or customer support teams to drive business or product changes.
B.S. or M.S. in Data Analytics, Business Statistics, Finance, Information Systems, or a related quantitative discipline; equivalent practical analytical experience considered.

Responsibilities

Analyze high-volume device telemetry and behavioral data to understand how, when, and why customers use specific smart home products on a daily basis.
Partner with Customer Operations and Technical Support to systematically audit troubleshooting calls, hardware failure rates, and customer friction points.
Translate real-world product issues and negative customer experiences into clearly defined product gaps, presenting data-backed optimization opportunities to core Product Managers.
Support core Product Managers by providing empirical data and usage baselines to inform 1-to-2 year product roadmaps and feature prioritization.
Operate as the central hub for product insights, collaborating daily with Supply Chain (on hardware reliability), Marketing (on feature adoption), Research (on user sentiment), and Operations (on field issues).
Synthesize disparate data streams into unified, scannable dashboards and operational metrics that accurately reflect the health and performance of the live product portfolio.
Lead the conceptualization and deployment of internal generative AI, search, or analytical tools designed to help internal teams query and understand complex product and business data more efficiently.
Build automated reporting mechanisms and data repositories that allow non-technical stakeholders to quickly extract trends regarding product usage and operational performance.