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Senior Product Manager - Core Data & Decision Intelligence

Target is hiring a Senior Product Manager - Core Data & Decision Intelligence. Level rates it ; you can apply on Target.

Level's read on this job

  • Level rates this AI product manager role Works on AI ●●●○: the daily work is on AI products, without building the model.
  • Level classes it as a senior role.
  • Target has 14,000+ other open roles on Level.
  • Posted in the last few days.

AI in this role

Senior Product Manager – Core Data and Decision Intelligence

Target in India | L6

About Us

As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America’s leading retailers.

Working at Target means the opportunity to help all families discover the joy of everyday life. Caring for our communities is woven into who we are, and we invest in the places we collectively live, work and play. We prioritize relationships, fuel and develop talent by creating growth opportunities, and succeed as one Target team. At our core, our purpose is ingrained in who we are, what we value, and how we work. It’s how we care, grow, and win together.

Target is investing in the next generation of intelligent store experiences that connect operational, digital and physical environments to create smarter outcomes for guests, team members and the business.

Our Core Intelligence Product teams are building the foundational capabilities that enable Target’s stores to understand what is happening, anticipate what matters, recommend the right actions, and continuously learn from outcomes.

About the Job – Senior Product Manager, Core Data and Decision Intelligence

What if a store could understand its operating environment in real time, recognize what matters most and intelligently recommend what should happen next?

That is the future our Core Data and Intelligence teams are working toward.

As a Senior Product Manager for Core Intelligence, you will build highly technical products that transform operational and physical signals into trusted intelligence that powers smarter Store decisions and experiences.

You will own a complex intelligence product end-to-end—from deeply understanding the problem and developing product strategy through discovery, experimentation, delivery and measurement of outcomes.

You will work side-by-side with Engineering and Data Science and partner with UX, Store Operations and other Product teams to build scalable capabilities that can power multiple workflows and experiences across Target.

Product Strategy & Ownership

  • Own the vision, strategy, roadmap and outcomes for a complex Core Intelligence product.
  • Develop a deep understanding of Store operations, users and the decisions your product is intended to improve.
  • Translate customer and business problems into clear product opportunities and hypotheses.
  • Balance immediate use cases with development of reusable capabilities that can scale across Target.
  • Define meaningful product health and outcome metrics and use them to drive prioritization and investment decisions.

Discovery & Intelligence Product Development

  • Lead continuous discovery with Engineering, Data Science, UX, Operations and consuming Product teams.
  • Explore how operational context, data science, AI/ML and emerging technologies can solve meaningful Store problems.
  • Design experiments and prototypes to test hypotheses before scaling solutions.
  • Partner closely with Data Science to define intelligence quality, confidence and feedback mechanisms.
  • Build products that continuously learn and improve through real-world outcomes.
  • Make thoughtful trade-offs across accuracy, latency, explainability, scalability and business value.

Product Delivery & Outcomes

  • Own and prioritize the product backlog while maintaining clear connection to strategy and outcomes.
  • Partner with Engineering and Data Science throughout discovery, development, launch and learning.
  • Make autonomous product decisions within your product area.
  • Establish adoption, product-health and outcome measures.
  • Continuously evaluate whether the product is solving the intended problem and adjust strategy based on evidence.
  • Ensure capabilities are reliable, reusable and extensible where appropriate.

Cross-Functional Leadership

  • Build trusted partnerships across Engineering, Data Science, UX, Store Operations and Product teams.
  • Influence partners and stakeholders through strong product thinking, evidence and storytelling.
  • Clearly communicate product strategy, customer problems, trade-offs and outcomes.
  • Navigate dependencies across a complex enterprise ecosystem.
  • Contribute to the broader Core Intelligence strategy and identify opportunities for reuse across Store experiences.

About You

  • 4-year college degree or equivalent experience.
  • 5+ years of Product Management or relevant product experience.
  • Experience owning complex, technical or data-intensive products.
  • Strong product discovery and problem-solving capabilities.
  • Comfortable partnering deeply with Engineering and Data Science.
  • Familiarity with AI/ML, data products, recommendation systems or intelligent platforms is preferred.
  • Ability to translate complex technology into intuitive customer and business outcomes.
  • Strong analytical thinking and ability to make decisions using imperfect information.
  • Excellent communication and cross-functional influence skills.
  • Curious, comfortable with ambiguity and energized by building products in emerging problem spaces.

Know More About Us here: 

How we rate this

Senior Product Manager - Core Data & Decision Intelligence at Target rates 74 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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