Senior Machine Learning Engineer (m/w/d)

Company Description

The Machine Learning Engineering (MLE) team in the NIQ Technology & Data department is an international team with colleagues working in Nuremberg, Malaysia, and Warsaw. Our MLEs work with data scientists in research teams and in cross-functional teams that include product experts, data analysts, software engineers, SREs, and front-end developers.
We are using various technologies over the various products and apply state-of-the-art science and machine learning techniques to provide data-driven intelligent solutions for our clients.

The MLE team actively encourages the personal growth of its members by offering continuous learning opportunities. The MLEs at NIQ Technology & Data department have a horizontal function. This will give you the opportunity to work in different product teams where you can gain experience In other business areas, meet new colleagues and become familiar with new methods and technologies.

This is a Warsaw based position - there is no travel required.

Job Description

Mission

• Optimize, standardize and implement data science and machine learning solutions at a large scale and in cloud-based environments
• Support the development of end-to-end analytical approaches based on product concepts
• Work with NIQ’s Point of Sale / third-party data to develop Data Science solutions for implementation and standardization in production environments
• Work closely with engineering, bridging the gap between Data Science and software engineers
• Screen the market for potential new/innovative Data Science approaches
• Actively share Data Science knowledge within our organization
• Represent NIQ’s MLE / MLEOps expertise at conferences and workshops.

Responsibilities

• Design, develop, test, deploy, maintain and enhance ML solutions using software engineering best practices
• Study and convert data science prototypes to production quality ML Solution
• Implement machine learning solutions at a large scale, in on-premises or cloud-based environments
• Implement end-to-end management of the model lifecycle using MLOps practices
• 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
• Contribute to Communities of Practice
• Present NIQ’s MLE / MLEOps expertise at conferences and workshops
• Support development of talent and organise required trainings

Qualifications

Qualifications

Essential skills

• Master or Bachelor degree that reflects computer science / engineering and statistical / mathematical skills
• Experience in machine learning software development and architectures for machine learning
• Solid experience with production-level code quality metrics and working closely with software and testing engineers
• Expert skills in Python and the respective Machine Learning ecosystem
• Expert skills in working in (big) database environments (RDBMS, Postgres, BigQuery)
• 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.
• Typically 5+ years of work experience

Desirable skills

• Solid experience with agile development practices
• Good to have experience in Machine learning frameworks such as MLflow
• Good to have experience or knowledge of kubeflow, Airflow, docker, Kubernetes
• Good to have experience in cloud computing environments (AWS, GCP)

• Prior experience in pricing, revenue assurance, media consumption patterns is valuable but not mandatory

About you

• Ability to think creatively in addressing analytical objectives
• Ability to translate and clearly communicate sophisticated analytical information to non-expert stakeholders and clients
• Act as a positive role model for the team by having a positive attitude and proactive approach while being approachable team player
• Already worked in leadership/mentoring positions or have the passion and ability to do so
• Ability to fluidly communicate in an English business environment

Additional Information

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

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Our commitment to Diversity, Equity, and Inclusion

NIQ is committed to reflecting the diversity of the clients, communities, and markets we measure within our own workforce. We exist to count everyone and are on a mission to systematically embed inclusion and diversity into all aspects of our workforce, measurement, and products. We enthusiastically invite candidates who share that mission to join us. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability status, age, marital status, protected veteran status or any other protected class. Our global non-discrimination policy covers these protected classes in every market in which we do business worldwide. Learn more about how we are driving diversity and inclusion in everything we do by visiting the NIQ News Center: https://nielseniq.com/global/en/news-center/diversity-inclusion