Quick Summary
Definition of North Star KPIs Build the experimentation muscle. Run real A/Bs on the parts of the product that matter. Kill features that don't earn their keep.
4+ years in product analytics or product data science, ideally at a SaaS company. PLG, SMB, or channel/partner-led experience is a real plus.
Established in 2022, Guardz rapidly emerged as a noteworthy player in the cybersecurity sphere, securing $85M in funding and rallying a dedicated team of 120 industry professionals. Our vision is to foster a safer digital landscape for small and medium businesses across the globe. To this end, we introduced our comprehensive all-in-one platform, and continue to grow and expand our team, our partnerships and our revenue.
This is a founding role. You won't inherit a dashboard graveyard or a half-built warehouse - you'll design the modeling layer, choose the tools, set the methodology, and decide what "good" looks like. You'll be the first product analyst, reporting to a centralized data team, and working directly with product leadership, go-to-market, UX designers & engineers.
Responsibilities
~1 min read- →Definition of North Star KPIs
- →Build the experimentation muscle. Run real A/Bs on the parts of the product that matter. Kill features that don't earn their keep.
- →Map the customer journey end-to-end - from signup to first deployment to first protected tenant to expansion - and tell us where the friction is, with numbers.
- →Analytics infrastructure: warehouse modeling, transformation layer, product analytics tool, BI. You'll have a strong opinion on the stack and the autonomy to build it.
- →Become the person leadership pings when they need to understand something quickly and correctly.
Requirements
~1 min read- 4+ years in product analytics or product data science, ideally at a SaaS company. PLG, SMB, or channel/partner-led experience is a real plus.
- Strong SQL - you've shipped the queries that quietly power half the company's decisions.
- Comfort in Python for analysis and automation.
- Experience with a transformation/pipeline tool (DBT or similar) and a clean modeling discipline.
- Real product analytics chops - funnels, retention, experimentation, segmentation. You can explain when not to A/B test as well as when to.
- An AI-native working style. You build small agents and prompts to do the boring parts of your job. You assume the answer is "this should be automated" until proven otherwise.
- High curiosity and a strong bias toward action. Founding-team energy.
Nice to Have
~1 min read- DBT specifically.
- Strong Python (stats, modeling, light ML).
- PostHog experience.
- Background in cybersecurity, channel sales, or B2B2B SaaS.
Location & Eligibility
Listing Details
- Posted
- June 2, 2026
- First seen
- June 2, 2026
- Last seen
- July 17, 2026
Posting Health
- Days active
- 30
- Repost count
- 0
- Trust Level
- 23%
- Scored at
- July 3, 2026
Signal breakdown
Please let Guardz know you found this job on Jobera.
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