Nielsen Connect empowers manufacturers and retailers to make bold decisions and transform their businesses with trusted data, solutions, and insights designed to drive progress. We collect and process billions of pieces of data every single day, transforming this raw information into cutting edge solutions powered by our unified platform – an open data ecosystem, built on Microsoft Azure. Our Connect platform is microservices-based, with all layers highly decoupled and focused, so we can move as quickly as technology evolves, and transform the consumer research industry in ways our clients have never seen before.

Job Description

Lead NLP Research Scientist

Lead Research Scientist who will work as part of the Nielsen Connect AI NLP Research Team.

The mission of the NLP (Natural Language Processing) Research Team is to Research, Develop and Deliver machine learning solutions that extract meaning and automate decision making from unstructured text and multi-modal data. Its aim is to provide our clients with higher quality, more timely and far reaching understanding of markets and consumers through the application of NLP.

You are an expert in applying NLP and machine learning to a wide range of business problems, and have proven experience with researching and deploying machine learning models applied to text data. We operate at scale, so you should be able to build models that can handle large, sparse and long tail datasets across multiple countries, categories and languages.

This role is responsible for the research and development of machine learning models to generate structured product attributes from ecommerce product data. You are an innovator at heart who is motivated by being set a challenging problem and can work as part of a close-knit team to invent cutting edge solutions which make a real difference to the business. You will not be afraid to learn and apply new techniques to solve a problem. You should have knowledge of and interest in the latest research and advancements in NLP, and, crucially, understand how to “take them out of the lab” to move beyond research to practical application.

Develop machine learning models to perform product data attribution from text and image
Perform feasibility studies and analyse large amounts of data
Work with internal business stakeholders to understand operational processes and requirements and translate into data driven solutions.
Research and develop machine learning models and algorithms which can solve defined business objectives to agreed success criteria
Apply rapid prototyping agile principles to quickly move models from research to scalable data products to be tested with end users
Design experiments to measure the impact on productivity of developed models
Document results and present findings to stakeholders across the business
Work as part of the wider NLP Research team, contributing to cross-project research and development of a shared research code framework




At least an MSc in a quantitative subject such as Statistics, Mathematics, Physics, Computer Science, AI or Machine Learning.
Minimal work experience of 5 years with evidence in related field
Experience at all stages of data science; problem definition, data acquisition & wrangling, modelling, feature engineering and deployment.
Deep Learning applied to text data using PyTorch, TensorFlow or a similar Deep Learning framework. Techniques used should include embeddings; convolutional networks; recurrent networks; sequence data.
Knowledge of the latest NLP algorithms, including FastText, transformer architectures such as BERT, and transfer learning applied to NLP
Experience and understanding of supervised and unsupervised learning; machine learning algorithms including neural networks, word embeddings, linear regression, decision trees, random forest, gradient boosted trees, SVM etc; NLP.
Languages and technologies: Python, PyTorch, scipy stack (pandas, numpy, matplotlib, Jupyter)
Coder with strong experience with building Python solutions using OOP principles using a Python IDE such as VS Code or PyCharm.
Version control using git and collaborative development tools such as Confluence.
Ability to work within an agile development framework, and experience of agile methodologies such as Scrum are desirable.
Working in a business to understand business needs, translate them into specific requirements, and build solutions which meet those requirements.
A good level of interpersonal and communication skills (English level B2 minimum).
Excellent written and verbal communication skills and experience of presenting findings to stakeholders.
Problem solving capabilities
Ability to manage projects and deliver to agreed deadlines
Intellectual curiosity and persistence to find answers to questions.
Able to understand scientific papers and develop the ideas in executable code

Educational level:

Master Degree

Level of experience (years):

Senior (5+ years of experience)

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