Machine Learning Engineer

Company 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.

Job Description

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

· Implement machine learning solutions at a large scale, in on-premises or cloud-based environments

· Create and improve methods and tools and contribute to best practices in the area of Data Science

· Foster ML related knowledge exchange within NIQ, especially around code quality and engineering best practices related knowledge exchange within NIQ

· Present NIQ’s MLE / DS expertise at conferences and workshops

Qualifications

· Master or Bachelor degree that reflects computer science / engineering and statistical / mathematical skills

· Typically 2+ years of work experience

· Solid experience with production-level code quality metrics and working closely with software and testing engineers

· Expert skills in Python and the respective statistical ecosystem

· Solid statistical skills:

• either in survey statistics (sampling, non-response adjustments, Bayesian statistics),
• or econometric modelling (program evaluation, forecasting, economic theory, panel data),
• or observational causal inference (potential outcomes, structural equation models, instrumental variables)
• or experimental design

· Experience working with docker

Additional Information

Soft Skills

· Ease of communication in an English-speaking business environment

· Be well-organised and flexible, and demonstrate self-confidence, decisiveness and commitment

· Good attention to detail – ensure all outputs are delivered professionally and accurate

· Mathematical thinking, strong analytical and problem-solving skills

Our Benefits

• Flexible working environment
• Volunteer time off
• LinkedIn Learning
• Employee-Assistance-Program (EAP)

NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and Guiding Principles: https://nielseniq.com/global/en/info/niqs-ai-safety-policies/

About NIQ

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.

For more information, visit NIQ.com

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Our commitment to Diversity, Equity, and Inclusion

At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence.  All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit the https://nielseniq.com/global/en/news-center/diversity-inclusion