Lead Data Scientist

Lead Data Scientist

Job Description

Join the team behind iconic brands like Huggies®, Kleenex®, Cottonelle®, Scott®, Kotex®, Poise®, Depend®, and Kimberly‑Clark Professional®.

At Kimberly‑Clark, you’ll find innovation, growth, and the opportunity to make a real impact.

You were made to create Better Care for a Better World—by designing new technologies, working with data, optimizing digital experiences, and delivering better, faster results.

Be part of a performance‑driven culture where technology has purpose, and where sustainability, inclusion, wellbeing, and career growth are integral.

It starts with YOU.

About You

In one of our technical roles, you’ll focus on winning with consumers and the market, while putting safety, mutual respect, and human dignity at the center.

The role involves understanding business problems, analyzing data, and defining success criteria while collaborating with engineering and architecture teams for data collection, harmonization, and cleansing.

It requires identifying suitable algorithms, exploring additional inputs to improve models, and building scalable, interpretable solutions that meet business needs.

Responsibilities include creating visualizations, presenting results to stakeholders, and applying Agile methodologies to deliver production-ready products.

The role also focuses on recommending new tools for data preparation, ensuring seamless integration of development and deployment, and curating code and artifact repositories.

Collaboration with AI strategists, DevOps, and SMEs is essential to assess data quality impacts, while innovative techniques and tools are developed across the AI lifecycle.

Additional duties include designing experiments with product teams, communicating findings effectively, applying machine learning and statistical methods for insights, and conducting research and troubleshooting complex challenges using advanced platforms such as Databricks and deep learning tools.

Required Qualifications


* Required 10+ years building scalable ML models and pipelines in cloud-based architectures (AWS, Azure, GCP).


* Expertise across supply chain, sales, marketing, revenue management, and enterprise ML solutions.


* Proficient in Python, SQL, and experienced with automated pipelines for data processing, training, deployment, and monitoring.


* Hands-on with Docker, Kubernetes, and ML tools like SageMaker, Azure ML, MLFlow, KubeFlow.


* Skilled in full AI lifecycle: predictive modeling, NLP, deep learning, advanced analytics, and governance.


* Strong knowledge of databases, microservices, REST APIs, CI/CD, source code management, and security.


* Agile practitioner with a can-do attitude, innovation mindset, and proven delivery in production environments.

To Be Considered
Click the Apply button and complete the online application process.

A member of our recruiting team will review your application and follow up if you seem like a great fit f...