Mid-level Data Scientist (Mandarin Speaking)

Short Summary

Mid-level Data Scientist (Mandarin Speaking) with NielsenIQ. Purpose of the role – mission: The Data Scientist role is responsible for designing and managing universe studies, setting up the extrapolation for Retail Panels, documenting methodologies, ensuring quality assurance, and monitoring key performance indicators (KPIs) related to Panel Health. This role requires a strong background in data analysis, statistical…

Key Details

• Position / opportunity: Mid-level Data Scientist (Mandarin Speaking)
• Organization: NielsenIQ
• Country / coverage: Malaysia
• Location: Kuala Lumpur, 14, Malaysia
• Work arrangement: On-site
• Opportunity type: Volunteer opportunities
• Sector: Health
• Compensation: Not specified
• Duration: Not specified
• Start date: 2026-07-14
• Application deadline: Not specified

Description

Purpose of the role – mission: The Data Scientist role is responsible for designing and managing universe studies, setting up the extrapolation for Retail Panels, documenting methodologies, ensuring quality assurance, and monitoring key performance indicators (KPIs) related to Panel Health. This role requires a strong background in data analysis, statistical modeling, and quality control processes as well as strong production system processes for PoS. This role supports the China market. Key activities: Methodology and Universe Studies: Design and manage universe studies, including project management. Document methodologies for transparency and provide clear explanations of existing methods. Review results of universe studies and insert changes in the POS Manager. Conduct impact analysis of universe studies. Design and simulate extrapolation setups for new panels and sign off on the designs. Quality Assurance: Optimize samples by analyzing shop contributions, detecting MDQC (Market Data Quality Check) outliers, meeting target sample requirements, and addressing issues like empty shops and slow sales. Detect and address systematic methodological issues and prepare cleanup impacts for critical findings (end-to-end). Modeling and Extrapolation: Model missing retailers completely outside the system and maintain complex models. Support the setup of modeling missing retailers in the system and hand over to Stat Ops for ongoing maintenance and execution. Implement new country-channel setups, including reviewing channel definitions, designing universes and samples, and providing setup instructions. Quality Monitoring: Resolve Level 2 methodology clarification issues. Monitor KPIs and conduct root cause analysis (RCA) for panel health, focusing on samples, missing retailers, universes, copy shops, and MDQC related to samples and extrapolation. Define and specify improvement points for panel health. Atleast 2-3 years of relevant experience Strong analytical and problem-solving skills. Proficiency in statistical modeling and data analysis. Experience with quality assurance and sample optimization. Ability to document and explain complex methodologies clearly. Familiarity with KPI monitoring and root cause analysis. Excellent communication and organizational skills. Ability to work independently and as part of a team. Knowing production processes for PoS Extensive experience of working in an international environment Strong quality orientation and solution driven Strong command of the English and Chinese language Extensive experience within Panel Quality value chain High knowledge about all PoS (RMS) value chains This role is ideal for individuals with a keen eye for detail and a passion for data science and quality assurance. If you enjoy working in a dynamic environment and have the skills listed above, we encourage you to apply for the Data Scientist position. Benefits: • Exciting work environment that brings people together. • Use the latest digital technologies. • Ongoing trainings to support your development. • Opportunities for personal and professional growth. • Great compensation linked to individual performance and company results. • Hybrid work Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certain administrative tasks that help streamline workflows. These tools are intended to improve efficiency and support fair and consistent evaluation based on job-related criteria. All use of AI is governed by NIQ’s principles of fairness, transparency, human oversight, and inclusion. Final hiring decisions are made exclusively by humans. NIQ regularly reviews its AI tools to help mitigate bias and ensure compliance with applicable laws and regulations. If you have questions, require accommodations, or wish to request human review were permitted by law, please contact your local HR representative. For more information, please visit NIQ’s AI Safety Policies and…

Responsibilities

• Purpose of the role – mission: The Data Scientist role is responsible for designing and managing universe studies, setting up the extrapolation for Retail Panels, documenting methodologies, ensuring quality assurance, and monitoring key performance…
• This role requires a strong background in data analysis, statistical modeling, and quality control processes as well as strong production system processes for PoS.
• This role supports the China market.
• Key activities: Methodology and Universe Studies: Design and manage universe studies, including project management.
• Document methodologies for transparency and provide clear explanations of existing methods.
• Review results of universe studies and insert changes in the POS Manager.

Requirements / Eligibility

• , and addressing issues like empty shops and slow sales.
• Detect and address systematic methodological issues and prepare cleanup impacts for critical findings (end-to-end).
• Modeling and Extrapolation: Model missing retailers completely outside the system and maintain complex models.
• Support the setup of modeling missing retailers in the system and hand over to Stat Ops for ongoing maintenance and execution.
• Implement new country-channel setups, including reviewing channel definitions, designing universes and samples, and providing setup instructions.

How To Apply

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