Product Manager - Insights & Analytics
About Qevlar AI
Qevlar is a B2B SaaS startup that strives to massively increase the productivity of cybersecurity teams. We develop AI Cybersecurity Analysts that augment Security Operations Centers (SOCs). Since our creation 2 years ago, we have:
Raised €14 million in seed funding led by EQT Ventures and Forgepoint Capital
Been incubated both by Microsoft (genAI studio) and Meta (AI program)
Deployed our solution to Global 500 companies and leading MSSPs in EMEA and NA
We're looking for a Product Manager to own a new product area: turning our platform data into insights, dashboards, and reporting that customers actually value.
About the role
Security teams need to understand what's happening in their environment, communicate value to stakeholders, and make informed decisions. Dashboards, analytics, and reporting are critical parts of this.
You'll own a greenfield product area focused on insights and visualization features. We need someone to talk to customers, identify what's useful, design the right experiences, and ship features people actually use.
This means spending time with security teams to understand their workflows, collaborating with design to build clear visualizations, and working with engineering to make it happen.
The hard parts: you're starting from scratch. The domain is broad. You need strong product instincts to identify what's valuable and ship iteratively without overbuilding.
What you'll do
Own the roadmap for platform insights, dashboards, and analytics features
Work directly with customers to understand what data and insights they need, and how they want to consume it
Collaborate with design to create visualizations that are clear, useful, and appropriate for different user types
Identify high-value opportunities by talking to users and analyzing platform data
Partner with engineering to define requirements, prioritize what's feasible, and ship iteratively
Track adoption and iterate based on how customers actually use these features
Who you are
Required:
3-6+ years as a Product Manager in analytics, BI, data visualization, or platform products
Strong experience designing dashboards and reports - you understand how to make data accessible and actionable for different user types
Comfortable working with raw data and analytics teams to define requirements and validate feasibility
Ability to take ambiguous problem spaces and structure them into concrete product opportunities
User-focused - you talk to customers, watch them work, and let their reality shape what you build
Clear communication skills - you can explain data concepts to non-technical users and translate business needs to engineers
Nice to have:
Security or cybersecurity operations background (helpful but not required)
Experience building analytics or BI products for technical users
You'll struggle here if:
You need well-defined requirements and clear direction before you can start
You can't handle ambiguity - this is a new product area with open questions
You're more interested in sophisticated analytics than useful, simple insights
You can't balance technical possibility with commercial viability
Why join us
Own a greenfield product area with direct impact on company growth and retention
Join a small product team where your decisions shape not just features but business strategy
Build products deployed at Global 500 companies and leading MSSPs
A company culture that values customer obsession, clarity over complexity, and shipping fast
Opportunity for equity and early ownership
We're flexible on location - you can either work from home or join your colleagues in our beautiful office in Paris' 9th arrondissement
If you're excited about turning platform data into customer value, we'd love to hear from you.
Hiring process
Intro Call
Product Interview (customer scenarios, visualisation/analytics depth)
Case Study (take-home exercise)
Meet the Team
- Locations
- Paris
- Remote status
- Hybrid
- Employment type
- Full-time
About Qevlar AI
Fully autonomous automation for defensive cybersecurity teams (SOC). Explainable AI. Agnostic approach. No playbooks needed.
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