Data Scientist

NielsenIQ; Vadodara; On-site; INR 900,000 - 1,500,000; Full time

Benefits offered by this job

Flexible working environment

Volunteer time off

Job summary

NIQ is seeking a Data Scientist to design and lead universe studies, set up extrapolation for Retail Panels, and model rawdata for non-coop retailers. The role requires strong data fluency, retail panel expertise, and ability to support root-cause analysis for client issues.

The position emphasizes documentation of methodologies, cross-team collaboration, and annual updates to sample targets, with responsibilities spanning design, validation, and maintenance of analytical processes in an

Qualifications

• Strong analytical and problem-solving skills.
• Proficiency in statistical modeling and data analysis.
• Ability to document and explain complex methodologies clearly.
• Familiarity with root cause analysis methods (such as 5_why method)
• 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 language

Responsibilities

• Design and lead universe studies, acting as a project manager for these studies.
• Document methodologies for transparency and provide clear explanations of selected methods.
• Validate the universe estimation.
• Conduct impact analysis of universe studies where relevant.
• Design and simulate extrapolation setups for new panels.
• In case of major change in the sample of a channel, redesign its extrapolation matrix, conduct impact analysis where relevant.
• Support StatOps team in case of minor events and data issues.
• Assess the feasibility of non-coop retailer rawdata modelling and design solutions.
• Once implemented, handover to Operation for ongoing maintenance and execution.
• Explain methodology of a Rawdata modelling to Commercial teams and Client Operation.

Skills

Analytical thinking

Statistical modeling

Documentation

Root cause analysis

Communication skills

Team collaboration

POS production processes

International experience

Quality orientation

English proficiency

Job description

The Data Scientist role is responsible for designing and leading universe studies, setting up the extrapolation for Retail Panels, discussing and designing rawdata modelling for non-coop retailers, and supporting root-cause analysis in case of client’s complaints when related to these activities.

This role requires strong data fluency, analytical skills with the ability to assess data relevance, and a deep understanding of retail panels and their value.

Key activities:

• Design and lead universe studies, acting as a "project manager" for these studies.


• Document methodologies for transparency and provide clear explanations of selected methods.


• Validate the universe estimation.


• Conduct impact analysis of universe studies where relevant.

Extrapolation:

• Design and simulate extrapolation setups for new panels.


• In case of major change in the sample of a channel, redesign its extrapolation matrix, conduct impact analysis where relevant.


• Support StatOps team in case of minor events (how to select a donor shop for a copy shop or a create shop, how to slightly update the extrapolation in case of e.g. empty cell, discuss quality issues / risks in case of weak / weaker sample).


• Assess the compliance of the existing design of extrapolation matrix and eventually recommend improvement (in the design, the sample size = recommend target for recruitment, etc.)


• Specify sample checks per country_channel and ensure that they are properly executed by Operation teams.


• Jointly with Operation, review the quality of the existing extrapolation and recommend / redesign if necessary (feedback loop from MDQC teams).


• Update the Target Sample File every year and in case of significant change in the universe or the sample.


• Assess the feasibility of non-coop retailer rawdata modelling outside of the system: business interest (in collaboration with Product), availability of data sources, usability of modelling components


• Design the solution, test the development, review the quality once implemented, review every year the relevancy of the solution


• Once implemented, handover to Operation for ongoing maintenance and execution.


• Support Commercial teams and Client Operation to explain the methodology of a Rawdata modelling.

Quality and Projects

• Implement new country-channel setups, including reviewing channel definitions, designing universes and samples, and providing setup instructions.


• Resolve Level 2 methodology clarification issues.


• Support Major Data Change required by a redesign recommended by Data Science (major change in the universe, major redesign of an extrapolation, major redesign of a rawdata modelling): support the definition of the action plan, support the client communication.


• Participate to Data Science regional and global projects

Qualifications

Strong analytical and problem-solving skills.

• Proficiency in statistical modeling and data analysis.


• Ability to document and explain complex methodologies clearly.


• Familiarity with root cause analysis methods (such as 5_why method)


• 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 language

This role is ideal for individuals with a keen eye for detail and a passion for data and data science.

Additional Information

• Flexible working environment


• Volunteer time off

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/

About NIQ

NIQ is the world's leading consumer intelligence company, delivering the most complete understanding of consumer buying behavior and revealing new pathways to growth. In 2023, NIQ combined with GfK, bringing together the two industry leaders with unparalleled global reach. With a holistic retail read and the most comprehensive consumer insights-delivered with advanced analytics through state-of-the-art platforms-delivered with advanced analytics, NIQ delivers the Full View™. NIQ is an Advent International portfolio company with operations in 100+ markets, covering more than 90% of the world’s population.

For more information, visit NIQ.com

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At NIQ, we are steadfast in our commitment to fostering an inclusive workplace that mirrors the rich diversity of the communities and markets we serve. We believe that embracing a wide range of perspectives drives innovation and excellence. All employment decisions at NIQ are made without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable laws. We invite individuals who share our dedication to inclusivity and equity to join us in making a meaningful impact. To learn more about our ongoing efforts in diversity and inclusion, please visit the https://nielseniq.com/global/en/news-center/diversity-inclusion

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