Sr. Product Manager
פורסם 17 ביוני · 0 מועמדים
התפקיד במילים פשוטות
התפקיד כולל בעלות מקצה לקצה על תחום מוצר עשיר ב-AI ונתונים, החל מאיתור צרכי לקוחות וחקירת נתונים ועד למדידת ביצועי המוצר לאחר השקתו. המנהל/ת י/תעבוד בשיתוף פעולה הדוק עם צוות מדעי הנתונים ויעצב/תעצב את חווית המשתמש באמצעות אב-טיפוסים ו-wireframes.
- 5+ years of B2B SaaS product management experience
- At least 2 years owning data- or AI-powered products
- Proven ability to partner with data scientists as a peer
- Strong data fluency and ability to query, interpret, and analyze product data directly (SQL familiarity)
- Track record of shipping ML or AI-powered features, including scoping models with data scientists
- Familiarity with LLM application design (prompts, evaluation, fallbacks)
- Background working with small data science teams
- Background or formal training in UX research, interaction design, or HCI
- Experience designing AI-powered or agent-based product features
חולץ מתיאור המשרה · מתעדכן אוטומטית
למי זה מתאים
התפקיד מתאים למנהלי מוצר בכירים עם ניסיון של 5+ שנים ב-B2B SaaS, מתוכן לפחות שנתיים במוצרים מבוססי נתונים או AI, ובעלי יכולת מוכחת לעבוד בשיתוף פעולה עם מדעני נתונים. הוא פחות מתאים למי שמחפש/ת תפקיד המתמקד אך ורק באסטרטגיה או בביצוע, שכן התפקיד דורש שילוב של שניהם.
תיאור המשרה המלא
המשרה המקורית · נשמר לעיוןCentrical is the Performance Intelligence OS for the frontline, the only platform that closes the action gap between data and behavior. Across sales, service, and operations teams, Centrical routes the right interventions to whoever needs them, employees, managers, and increasingly AI agents, at every stage of the employee lifecycle.
We are looking for a Senior Product Manager to own an AI- and data-rich domain end-to-end, from customer signal and data exploration through to shipped, measured product.
This is a hands-on, builder role with two defining traits: deep partnership with our Data Science team, and user-experience craft that shapes feature flows and interactions. You will run your own analysis, bring sharp hypotheses to Data Science, and iterate on user experience through wireframes and prototypes. You will work closely with the Head of Product on portfolio direction while operating with high autonomy in your own area.
The role sits at the intersection of four competencies: senior product judgment, deep data fluency and partnership with Data Science, builder muscle to test hypotheses cheaply, and strong UX instincts to shape user-facing flows. We do not separate “discovery PMs” from “delivery PMs,” or strategic thinkers from builders. The role expects all of it.
Responsibilities:
Own an AI- and data-rich product domain end-to-end, from problem framing through shipped, measured outcome
Run discovery that combines customer conversations, data exploration, and rapid prototyping
Drive the data side of discovery: explore data, size opportunities, and shape hypotheses, both independently and alongside Data Science as the depth of the question demands
Build working prototypes (HTML, LLM-based stand-ins, scripts on real data) to validate value, flow, and experience before committing to engineering or visual design
Produce wireframes and multiple UX options for a feature, then partner with our product designer on the visual craft for production
Partner with Data Science as a peer: co-scope models, co-design feature definitions and labels, co-evaluate quality from both ML and user-experience angles
Write specs that pair concise written requirements with interactive prototypes
Define success criteria, design experiments, measure shipped outcomes, and iterate or kill based on what you see
Use AI tools actively to accelerate analysis, prototyping, and synthesis
Influence product strategy with well-reasoned, evidence-backed positions
Requirements:
5+ years of B2B SaaS product management experience, with at least 2 years owning data- or AI-powered products
Proven ability to partner with data scientists as a peer, with concrete examples of joint ideation rather than spec-and-handoff relationships
Strong data fluency: comfortable querying, interpreting, and analyzing product data directly. Familiarity with SQL is part of this, but the bar is the ability to think clearly with data, not a specific tool
Track record of shipping ML or AI-powered features, including at least one where you helped scope the model with a data scientist
Statistical literacy: experiment design, sample sizing, the difference between correlation and causation, and when ML is not the right tool
Strong UX instincts: comfortable wireframing, iterating on user experience, and translating customer research into product decisions. You shape what gets designed, but you don’t own visual design
Comfortable building prototypes with modern AI-assisted tools (Claude, Cursor, Lovable, v0, or similar)
Strong written and verbal communication, able to explain trade-offs clearly to Engineering, Design, Data Science, and senior stakeholders
Self-directed: in a small team, you sequence your own work and do not need a manager to prioritize your week
Bachelor’s degree in Computer Science, Engineering, Industrial Engineering, Information Systems, Math, Statistics, or a related quantitative field, or equivalent experience
Fluent English
Nice to have:
Experience with workforce, contact center, HR, or enterprise B2B domains
Familiarity with LLM application design (prompts, evaluation, fallbacks)
Background working with small data science teams where leverage matters more than scale
Background or formal training in UX research, interaction design, or HCI
Experience designing AI-powered or agent-based product features
Centrical is an equal opportunity employer. We welcome applicants of all backgrounds.
Please send your resume to: jobs@centrical.com
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שאלות על המשרה
- המשרה לא ציינה שכר. אנחנו מציגים שכר רק כשהמעסיק מפרסם אותו.
- 5+ years of B2B SaaS product management experience, At least 2 years owning data- or AI-powered products, Proven ability to partner with data scientists as a peer, Strong data fluency and ability to query, interpret, and analyze product data directly (SQL familiarity), Track record of shipping ML or AI-powered features, including scoping models with data scientists