Job Description

NielsenIQ’s Innovation Team is growing our Machine Learning capabilities and is now looking to hire a number of applied research scientists in Spain. These individuals will be responsible for analyzing data, researching the most appropriate techniques, and the development, testing, support and delivery of proof of concepts to resolve real-world and large-scale challenging problems. Both data and software must be developed and maintained with high-quality standards and minimal defects. 

What you’ll do

• Develop and apply machine learning innovations with minimal technical supervision.

• Perform feasibility studies and analyse data to determine the most appropriate solution.

• Work on many different data challenges, always ensuring a combination of simplicity, scalability, reproducibility and maintainability within the ML solutions and source code. 

• Understand the requirements from stakeholders and be able to communicate results and conclusions in a way that is accurate, clear and winsome. 

• To work as a member of a team, encouraging team building, motivation and cultivating effective team relations. 

We’re looking for people who have

• Bachelor's degree in Computer Science or an equivalent numerate discipline

• Fundamentals: Computer science, Linear algebra, calculus, probability and statistics

• Experience in Machine Learning and Deep Learning 

• Experience in Computer Vision and Natural Language Processing or at least in one of two fields

• Experience working with large real world datasets and scalable ML solutions 

• EDA analysis and practical hands-on experience with datasets, ML models and evaluations

• Background in applying latest ML/DL/CV/NLP advances to to real world problems 

• Able to understand scientific papers and develop the idea into executable code

• Experience integrating ML solutions as part of larger business products 

• Languages and technologies: Python, pandas, scipy, PyTorch, Tensorflow, sklearn, Trax, nltk, opencv

• Analytical mindset, problem solving and logical thinking capabilities

• Proactive attitude, constructive, intellectual curiosity and persistence to find answers to questions

• A good level of interpersonal and communication skills (English level B2 minimum) 

• Ability to maintain fluent written and oral communication 

• Strong ability to meet deadlines

• Keen to work as part of a diverse team of international colleagues and in a global inclusive culture

• A minimum of 7 years’ experience with evidence in a related field

Desired Skills

• Masters degree in one of the above mentioned fields

• Some experience in MLOPs and deployment of AI/ML solutions in the cloud

• Some experience in participating in Open Source projects

• Previous experience in retail, consumer, ecommerce, business, FMCG products (NielsenIQ portfolio)

• A grasp of databases (SQL, ElasticSearch, Solr)

• Agile methodologies development (SCRUM)

Additional Information

All your information will be kept confidential according to EEO guidelines.

About NielsenIQ 

NielsenIQ is a global measurement and data analytics company that provides the most complete and trusted view available of consumers and markets worldwide. We provide consumer packaged goods manufacturers/fast-moving consumer goods and retailers with accurate, actionable information and insights and a complete picture of the complex and changing marketplace that companies need to innovate and grow. Our approach marries proprietary NielsenIQ data with other data sources to help clients around the world understand what’s happening now, what’s happening next, and how to best act on this knowledge. We like to be in the middle of the action. That’s why you can find us at work in over 90 countries, covering more than 90% of the world’s population. For more information, visit www.niq.com.

NielsenIQ is committed to hiring and retaining a diverse workforce. 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.