Product Operations Manager
The Product Operations Manager drives operational excellence across product lines by analyzing customer feedback and product usage, building dashboards, improving processes, and aligning product, engineering, and field stakeholders. Requires 6+ years in business or data analysis and strong SQL, reporting, and communication skills.
About the job
Responsibilities
- Analyze and synthesize customer and partner feedback, product usage metrics, and other data sources to identify customer pain points.
- Design and maintain reports and dashboards that surface key metrics and trends.
- Influence product and engineering decisions using quantitative and qualitative analysis.
- Partner with operations teams to define metrics, automate reporting, and improve processes.
- Organize and monitor key results across product lines, communicating progress and blockers.
- Deliver ambiguous projects with incomplete data.
- Facilitate stakeholder syncs and cross-departmental alignment.
Requirements
- 6+ years of experience in a business analyst or data analyst role.
- Experience with SQL and Microsoft Excel.
- Experience building data pipelines using SQL, Python, R, or Scala.
- Experience creating dashboards and data visualizations with Tableau, Salesforce, Power BI, and/or Data Studio.
- Ability to communicate complex analysis and modeling to executives and department leadership.
- Enterprise software, SaaS, and B2B experience preferred.
- Experience with customer-facing support systems, including in-app help centers, case and form submission flows, and self-help features.
- Strong communication, presentation, stakeholder alignment, and prioritization skills.
- Experience leading update syncs; Agile, Scrum, and Jira experience preferred.
- Entrepreneurial, detail-oriented, and adaptable approach.
Compensation and Benefits
- Comprehensive benefits and perks are offered, with details varying by region.
Skills
SQL, Excel, Python, R, Scala, Tableau, Salesforce, Power BI, Google Data Studio, Agile, Scrum, Jira, Data Pipelines, Data Visualization
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