Senior Manager, Data Products Owner

Description

Kenvue is currently recruiting for a:

Senior Manager, Data Products Owner

What we do

At Kenvue , we realize the extraordinary power of everyday care.

Built on over a century of heritage and rooted in science, we're the house of iconic brands - including NEUTROGENA®, AVEENO®, TYLENOL®, LISTERINE®, JOHNSON'S® and BAND-AID® that you already know and love.

Science is our passion; care is our talent.

Who We Are

Our global team is ~ 22,000 brilliant people with a workplace culture where every voice matters, and every contribution is appreciated.

We are passionate about insights, innovation and committed to delivering the best products to our customers.

With expertise and empathy, being a Kenvuer means having the power to impact millions of people every day.

We put people first, care fiercely, earn trust with science and solve with courage - and have brilliant opportunities waiting for you! Join us in shaping our future-and yours.

For more information , click here .

Role reports to:
Sr Director Global Data 360 Products

Location:
North America, United States, New Jersey, Summit

Work Location:
Hybrid

What you will do

As a Product Owner, Data Products, you will be responsible for leading the development and deployment of data-driven products powered by digital, artificial intelligence and analytics technologies.

You will work closely with cross-functional teams, including data scientists, software engineers, product managers, and business stakeholders to define product vision, strategy, and execution.

Responsibilities:


* Product Vision and Strategy: Collaborate with stakeholders to define the product vision, goals, and roadmap for Digital, Data and AI products that align with business objectives


* Requirements Gathering: Work closely with business units to understand their needs and translate them into clear and actionable product requirements


* Data Management: Oversee data collection, storage, and preprocessing to ensure data quality and availability for training and model deployment


* Machine Learning Models: Coordinate with data scientists and ML engineers to design, develop, and deploy machine learning models that power AI data products


* Product Development: Lead the end-to-end product development process, including design, development, testing, and deployment of AI data products


* User Experience: Collaborate with user experience (UX) designers to create intuitive and user-friendly interfaces for AI data products


* Performance Monitoring: Establish metrics and tracking mechanisms to measure the performance and impact of AI data products


* Product Iteration and Improvement: Continuously iterate and improve data products based on user feedback and performance insights


* Market Analysis: Conduct market research and competitive analysis to identify opportunities and stay abreast of industry trends


* Risk Management: Identify potential risks and challenges related to data ...