Lead DNA MLOps and Data Science

Kenvue•Summit, NJ

15h•Onsite

About The Position

Kenvue Brands LLC is seeking a Lead DNA MLOps and Data Science professional to work closely with cross-functional teams to deliver scalable Artificial Intelligence (AI) solutions. This role involves developing, deploying, and maintaining these solutions with a focus on optimizing code, utilizing shared libraries, and documenting processes. The Lead will advocate for and implement a global MLOps model, design automation processes, and leverage tools like Databricks and Snowflake to build efficient ML pipelines and manage large-scale datasets. The position also requires collaborating with business stakeholders, serving as a Subject Matter Expert (SME) on the data science platform, mentoring team members, and researching the latest technologies to drive business value and improve team performance.

Requirements

Bachelor’s degree in Computer Science, Data Science, Machine Learning, Mathematics, Statistics, Economics, or related fields
5 years of experience in the job offered or in a Lead DNA MLOps and Data Science-related occupation.

Responsibilities

Work closely with cross-functional teams of business partners, data scientists, data engineers, solution architects, and data architects to rapidly deliver scalable Artificial Intelligence (AI) solutions and optimizations.
Develop, deploy, and maintain these solutions with a focus on optimizing data queries, refactoring code, utilizing shared libraries, and documenting processes and solution artifacts.
Advocate for and implement a global MLOps model across project teams to ensure standardization and consistency in AI solution design, research and development, deployment, and maintenance.
Design and implement automation processes throughout each MLOps project phase, emphasizing the development, testing, and adoption of reusable code libraries.
Leverage tools like Databricks to build autonomous, scalable, high-performance, and cost-effective ML pipelines.
Design and optimize Snowflake queries to ensure efficient access to large-scale datasets, integrate Snowflake with ML tools and frameworks, and maintain data quality and governance standards throughout the pipeline lifecycle.
Build and maintain robust ETL pipelines for efficient data processing.
Collaborate with business stakeholders and AI project teams to understand business requirements, develop scalable AI solutions, and communicate their value to business partners.
Serve as a Subject Matter Expert (SME) on best practices for leveraging the team’s global data science platform to drive MLOps processes and reduce the cost of AI projects.
Mentor and lead team members, including university students in co-op and internship programs.
Continuously research and promote the latest technologies, design patterns, and best practice delivery models to drive business value and improve team performance, processes, and platforms.
Apply innovative thinking in all aspects of work, consistently seeking the most effective ways to support teams and business partners.