Data Scientist

Description

Who We Are

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.

Our global team is made by 22,000 diverse and brilliant people, passionate about insights, innovation and committed to deliver the best products to our customers.

With expertise and empathy, being a Kenvuer means to have the power to impact life of 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.

What You Will Do

The Data Scientist will lead the Data Science/AI/ML work, drive advanced analytics initiatives, and contribute to the strategic vision of data-driven decision-making within the organization.

You will collaborate with cross-functional teams, including data engineers, business analysts, and product managers, to develop innovative data solutions and insights that impact business outcomes positively.

With a focus on applying operations research techniques to solve business problems, you will be a hand-on contributor for the data science team, driving advanced analytics initiatives to deliver innovative solutions.

Responsibilities:


* Technical contribution: Provide technical expertise to the data science team collaborating with data scientists on projects and methodologies.

Lead and manage complex data science projects from ideation to implementation, ensuring timely delivery and high-quality outcomes.


* Modeling and Analysis: Develop and deploy sophisticated simulation and optimization model using open source and commercial solvers.


* Data Exploration: Conduct in-depth exploratory data analysis to understand patterns, trends, and anomalies that can lead to valuable business insights.


* Algorithm Selection and Analytic formulation: Identify and recommend appropriate machine learning algorithms and techniques for specific business problems.


* Innovation and Research: Stay up-to-date with the latest advancements in Operations Research and apply cutting-edge techniques to enhance analytical capabilities.


* External partner engagement: Evaluation and selection of external vendors partners for data science and machine learning.

Working closely with the selected partner to oversee the technical and business outcomes.


* Collaboration: Collaborate with stakeholders to understand business challenges, align data science initiatives with business goals, and communicate results effectively.


* Data Governance and Ethics: Ensure compliance with data governance policies, privacy regulations, and ethical considerations related to data science projects.


* Continuous Improvement: Promote a culture of continuous learnin...