Job Purpose :
As a Lead Data Scientist within the Data Science Methods team in the NIQ Product organization, you will drive definition and support of new products and methods development, and improvement initiatives. This position focuses on innovation in data processing methods for retail measurement and automation of existing statistical procedures.
Job Responsibilities :
- Define, plan and execute analyses regarding innovation initiatives, methodology development, standards, and KPIs development and implementation.
- Prototype solutions and support pilot programs for R&D purposes, including trend analyses, representation / sampling, bias reduction, indirect estimation, data integration, automation, and generalization.
- Test-driven development of scalable data processing applications.
- Deliver high quality documentation of new methodologies and best practices.
- Collaborate with experienced Developers, Data Scientists, and Technology engineers.
- Support various Operations team as main users of our solutions.
- Engage with stakeholders on scope, execution, data exchange, and outcomes for assigned projects.
- Participate in multiple projects simultaneously.
Machine Learning & Artificial Intelligence :
Machine Learning : Knowledge of various algorithms and their appropriate application for prediction and classification.Deep Learning : Understanding of neural networks and deep learning frameworks like TensorFlow and PyTorch.Data Visualization & Presentation :
Data Visualization : The ability to create clear and compelling charts and graphs using tools like Tableau, Power BI, or Matplotlib to communicate findings to stakeholders.Databases & Cloud :
Database Management : Proficiency with both SQL and NoSQL databases (like MongoDB) for data storage and retrieval.Cloud Computing : Experience with cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, and Google CloudQualifications : Requirements :
Essential :
PhD degree in Statistics, with outstanding analytical expertise and strong technical skills.Extensive experience in trend analyses, multivariate statistics (parametric / non-parametric), sampling, bias reduction, indirect estimation, data aggregation techniques, automation, and generalization.High proficiency in Python programming language including data analysis and statistical packages (Pandas, NumPy, Scikit-Learn). Good familiarity with Python standard library, especially unittest and argparse modules.Experience with Spark or other big data processing solutions.Experience in machine learning.Experience with cloud computing and storage (MS Azure preferred).Experience with Docker and Linux command line.Ability to quickly manipulate, analyze, and interpret large data sources.Strong communication / writing skills with good English (working in a remote team with a global footprint).Preferred :
Experience in NIQ methodologies, data collection, platforms, research processes, and operations.(ref : hirist.tech)