NielsenIQ
Technology
ResearchScientist
Neural analysis suggests this role is
optimal for mid candidates.
“Research Scientist at NielsenIQ. Skills: Data science, Data engineering, ML/AI, Business intelligence. Develop and implement machine learning models. Design and build data pipelines”
Industry & Context.
What They're Looking For.
Must Have
Master's degree, 3-6 years experience, SQL proficiency, Python or R proficiency
Nice to Have
PhD preferred, Experience with ML frameworks, Cloud platform certifications
What You'll Do.
Develop and implement machine learning models
Design and build data pipelines
Create and maintain business intelligence dashboards
Perform quantitative analysis
Collaborate with stakeholders
How You'll Work.
Team & Collaboration
Cross-functional teams
Full Job Description
#LI-hybrid We are a team of passionate, curious and diverse professionals who care about each other, our work, our company and the world. We are looking for someone who combines skill in machine learning with an ability to connect with people and see the wider context for a range of business problems. You will be responsible for assessing state-of-the-art techniques, researching novel ideas to improve them, and applying them to large scale problems, mainly in the domain of recommender systems and NLP (from semantic search to deep research agents). To solve problems effectively, you will need to be able to build relationships and understand the business context in which we are operating. This position will suit someone who has a deep understanding of machine learning and is comfortable presenting clearly and winsomely to a non-technical audience. NielsenIQ helps companies to meet the needs of people all over the world for food, health, hygiene, tech and durable products. Since 1923, NIQ has moved measurement forward for industries and economies across the globe. This position opens the opportunity to research and apply state-of-the-art AI/ML techniques to strategic global projects. * Research, evaluate, and adapt state-of-the-art techniques to solve large-scale AI problems. * Fine-tune and evaluate Transformer-based models and embedding models for domain-specific applications. * Contribute to research initiatives in Information Retrieval, Product Matching, Recommendation Systems, and Generative AI. * Collaborate with technical colleagues on the integration of ML solutions. * Contribute to scientific publications, patents, and innovation initiatives. Maintain software and data assets following high-quality engineering standards * Develop and apply machine learning innovations to business problems with moderate technical supervision. * Assess experimental results and determine their applicability to real-world business challenges. * Understand stakeholder requirements
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