NielsenIQ: Data Science - Manager — Seoul, 11, Korea, republic of
NielsenIQ lists a Data Science - Manager opening in Seoul, 11, Korea, republic of. The position is listed as full-time. The job description covers stakeholder management, communication.
Recruitment overview
| Organisation | NielsenIQ |
|---|---|
| Post / role | Data Science - Manager |
| Employment type | Full-time |
| Notification / job ID | R26_0012545|KR |
| Job location | Seoul, 11, Korea, republic of |
| Work arrangement | On-site |
| Educational qualification | Degree / qualification: Bachelor’s degree or above in Statistics, Mathematics, Economics, Data Science, or a related field |
| Experience required | 5+ years of experience in FMCG, retail measurement, consumer analytics, or related industries |
| Salary / stipend | See employer notice for pay details |
| Last date to apply | See official notice |
About NielsenIQ
NielsenIQ, also known as NIQ, works in consumer intelligence and retail measurement. Its employer material describes using market information, consumer insights and analytics to help businesses understand buying behaviour. Its data operations address the accuracy and completeness of information behind client reports, while analytical services interpret that information. The business connects details about products and retail activity with broader views of markets, giving organisations evidence for understanding demand and making commercial decisions.
The position and its setting
NielsenIQ lists Data Science - Manager in Seoul, 11, Korea, republic of, under reference R26_0012545|KR. The details below separate the work described by the employer from essential conditions, preferred experience and practical preparation advice.
- Employment type: Full-time
- Employer listing date: 20 October 2026
- Brands: NielsenIQ
- Job Family: Predictive Analytics/Business Intelligence
Responsibilities and work described
- Development: and maintain data models for FMCG / retail measurement in the Korean market
- Design, validate, and refine Universe setting and projection methodologies based on panel data
- Execution: data cleaning, processing, and quality validation to ensure robust output
- Collaboration: with internal teams to define analytical approaches and methodologies for client projects
- Translate analytical findings into clear, structured storytelling for client communication
- Present reasoning behind methodologies, assumptions, and outputs to clients
- Continuously improve data quality, projection accuracy, and modeling approaches
- Management: stakeholder expectations and contribute to effective project delivery
Essential requirements and candidate background
- Bachelor’s degree or above in Statistics, Mathematics, Economics, Data Science, or a related field
- 5+ years of experience in FMCG, retail measurement, consumer analytics, or related industries
- Experience: Python for data analysis and modeling (required)
- Understanding: data processing, statistical concepts, and modeling fundamentals
- Experience working with SQL and large-scale datasets
- English communication skills (both written and spoken) — ability to effectively communicate with global teams and explain analytical outputs to clients
Preferred experience and additional strengths
- Experience: consumer panel data, retail measurement, or similar datasets
- Experience: Universe building and projection methodologies
- Prior experience working in a project-based, team-driven environment
- Exposure: stakeholder and client-facing roles
Location, schedule and contract conditions
For this overseas or regional listing, confirm work authorisation and any location restrictions with the employer. The location does not establish visa sponsorship or permission to work remotely from India.
- Work arrangement: On-site
- Advertised location: Seoul, 11, Korea, republic of
Benefits mentioned by the employer
- 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 Guiding Principles: https://nielseniq.com/global/en/info/niqs-ai-safety-policies/
Pay and application dates
A verified salary figure is not established in this article. An online estimate for another Data Science - Manager vacancy is not an offer for reference R26_0012545|KR; use the employer’s own pay disclosure and recruitment communication.
A closing date is not confirmed in this article. Check the current employer page before submitting: an undated posting can change or be withdrawn.
How to apply to NielsenIQ
Applications follow the official employer page linked below.
Open the official NielsenIQ posting below and match the title and reference R26_0012545|KR.
Compare your qualifications and experience with the essential conditions for the Seoul, 11, Korea, republic of position, then read the preferred criteria separately.
Prepare an accurate CV and the supporting items requested in that employer’s application. Provide only information and documents you are authorised to share.
Use the employer’s application option, complete the required fields and review the submission. Retain the acknowledgement when one is provided. Job Alerts World does not receive the application.
Practical preparation: Python
Python work is easier to assess through a concrete example than a list of libraries. Explain the problem, the input data, the parts you implemented and how you checked the output. Include a repository or a short technical note when you can share it.
Relevant skills
- Python
- SQL
- stakeholder management
- communication
- data analysis
Important links
| Official notification / job description | Open official page |
|---|---|
| Online application portal | Open official page |
Read the complete official notice before applying. Availability and requirements can change.
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