NielsenIQ
Market Research
MachineLearningEngineer
Neural analysis suggests this role is
optimal for mid candidates.
“Machine Learning Engineer at NielsenIQ. Skills: Machine Learning, Deep Learning, MLOps. Design and implement ML models. Develop and maintain ML pipelines”
What You'll Achieve.
Deliver high-quality ML solutions; Improve model accuracy; Enhance system efficiency
Industry & Context.
Problem-solving; Analytical skills
What They're Looking For.
Must Have
Bachelor's degree in Computer Science, 5+ years of experience in ML, Experience with Python, Experience with deep learning frameworks, Experience with large-scale data processing
Nice to Have
Master's degree or PhD, Experience with distributed systems, Experience with cloud platforms, Experience with MLOps
What You'll Do.
Design and implement ML models
Develop and maintain ML pipelines
Collaborate with engineering teams
Stay current with ML research
Contribute to system design
Optimize model performance
Deploy models to production
How You'll Work.
Team & Collaboration
Cross-functional teams; Engineering teams
Communication Scope
Technical presentations
Full Job Description
NIQ is the world’s leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights—delivered with advanced analytics through state-of-the-art platforms—NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population. You will join international and collaborative team, with colleagues based across the US, Germany, Poland, and Italy. The team delivers innovative solutions in the field of market research, with a strong focus on brand management. Our team combines advanced statistical modeling with hands-on software development. We start by designing and validating Proof of Concepts (PoCs) that address real business challenges, and then transform these prototypes into robust, scalable products used globally. This means your work will not end at experimentation—you will be directly involved in delivering and maintaining production-grade solutions that create impact at scale. As a Machine Learning Engineer, your role bridges data science and software engineering. You will take ownership of turning PoC models into reliable, maintainable, and scalable systems. This includes designing production architectures, optimizing performance, ensuring code quality, and enabling seamless deployment across global environments. This is a role for someone who enjoys both experimentation and engineering—someone who wants to see their models evolve from initial ideas into fully operational products used worldwide. Responsibilities · Design, develop, test, deploy, maintain and enhance data science solutions using software engineering best practices · Study and convert data science prototypes to production quality DS/ML Solution · Impleme
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