Lead Data Scientist

About this role

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Skills you'll use

What you'll do

• Research and develop new methodologies, research directions, prototype solutions, and quantify their improvement with rigorous scientific methods in the ML/AI space.
• Own all the phases of an R&D project or process improvement, including conceptualization, design, prototyping, documentation, deployment, and monitoring.
• Work closely and collaborate with experienced teams in operations, technology, other data scientists, and internal stakeholders during all phases of a project.
• Deliver high quality, academic publication-level, documentation of new methodologies and best practices.
• Engage with stakeholders on objectives, scope, execution, data exchange, and outcomes for assigned projects.
• Participate in and actively contribute to multiple projects simultaneously.
• Bachelors in Data Science, Mathematics, Statistics, Engineering, Computer Science, or related field & experience, with outstanding analytical expertise and strong technical skills. At least 7 years of relevant experience.
• Domain expert knowledge in multiple areas of the following: programming, software engineering / UI & UX / multivariate statistics (parametric/non-parametric) / machine learning / deep learning & Agentic AI / trend & time-series analysis / sampling theory.
• Critical and innovative thinking coupled with strong analytical skills focused on experimentation and hypothesis testing.
• High proficiency in Python programming (without AI assistance) and working with large-scale databases (e.g., SQL, Hadoop, pySpark, etc), statistical packages (Pandas, NumPy, Scikit-Learn), and unit testing. Experience with AzureML, DataBricks, and CI/CD (Docker, Unix, AKS) best practices.

Who can apply

• Critical and innovative thinking coupled with strong analytical skills focused on experimentation and hypothesis testing.
• High proficiency in Python programming (without AI assistance) and working with large-scale databases (e.g., SQL, Hadoop, pySpark, etc), statistical packages (Pandas, NumPy, Scikit-Learn), and unit testing. Experience with AzureML, DataBricks, and CI/CD (Docker, Unix, AKS) best practices.
• Able to work in virtual environment and comfortable with git (Github) processes, including PRs and code conflict resolution.
• Strong communication, presentation and collaboration skills in the English language with a record of written materials and public presentations (e.g., papers, conferences, patents, tutorials, substack, etc).
• A continuously learner willing to experiment and adopt new technologies and tools.
• Experience in NIQ processes and methodologies, such as data collection, platforms, research processes, and operations.
• Flexible working environment
• Volunteer time off

About NielsenIQ

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