Machine Learning Engineer

NielsenIQ | Madrid | ES

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Mission Develop Marketing Science solutions in the area of media analytics Support the product development during concept testing phases, scaling and production Transform proofs-of-concept into scalable, production-ready code Responsibilities Develop, implement and standardize marketing science solutions in proofs-of-concept and prototypes Continuously improve the efficiency of the marketing science products (e.g. ensure quality by adherence to coding guidelines, documentation and reproducibility) Optimize marketing science models using code optimization, high-performance computing and real-time techniques Build analytical pipelines at scale using cloud services, containerized applications and distributed systems Identify best practices and create continuous improvement of tools and methods Closely collaborate with Product Owners, Modellers, Marketing Scientists and Front End Software Engineers Qualifications Bachelor or Master degree that reflects strong statistical/mathematical/computer science skills Strong expertize in Python usage - at least 3 years of development Understanding of R Experienced in statistical modelling on top of predictive modeling Able to manage code deployments (experience with GIT) Basic understanding of Dockerization – building and managing docker images Experienced with creating, managing and/or maintaining code documentation Solid skills concerning performance optimization and scalability (e.g., parallelization, code optimization, functions as a service) Ability to present and explain complex concepts to less experienced colleagues Soft Skills Strong analytical and problem-solving skills Able to work independently Good attention to detail – ensure all outputs are delivered professionally and accurate Good interpersonal skills – treat others with respect, be cooperative, friendly and considerate of others. Be a good role model, help to build teamwork and team spirit Well-organised and flexible, and demonstrate self-confidence, decisiveness and commitment able to work alone without constant support, and well organized Ease of communication in an English-speaking business environment Additional Information Hybrid : our team goes 1 per week at Madrid office - we offer a Flexible working mode Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) 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 Want to keep up with our latest updates? Follow us on: LinkedIn | Instagram | Twitter | Facebook 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 diversity page at NIQ. J-18808-Ljbffr

Information :

  • Company : NielsenIQ
  • Position : Machine Learning Engineer
  • Location : Madrid
  • Country : ES

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Post Date : 2025-10-27 | Expired Date : 2025-11-26