JR Data Scientist

at  NIELSENIQ

Company Description
As the world’s largest research organization, Nielsen is powered by talented creative scientists. Our JR Data Scientist come from diverse disciplines such as statistics, research methodology, mathematics, business, engineering, physics and demography. These professionals drive innovation, new product ideation, develops complex analysis and delivery of data insights to measure what consumers buy.
Job Description
A JR Data Scientist is responsible for ensuring that the activities of Universe Estimation and Sample Design are carried out on time and according to corporate standards, supported by the supervision of his immediate superior.

Responsibilities

• Guarantee the quality and integrity of the data used in the analyses.
• Use statistical methodologies to analyze data.
• Innovate from a critical review of statistical designs and market needs.
• Strong capacity for statistical data analysis.
• Experience in large-scale sampling and/or surveys.
• Knowledge of Machine Learning/Neural Networks

Qualifications
Ability to analyze statistical processes, self-directed, proactive and with leadership. He generates ideas for improvement, does things differently, is passionate about being part of a high-performing team, and willing to support special projects or initiatives as needed.

Requirements

• Degree in Actuary, Statistics, Applied Mathematics or similar.
• Experience 0 to 1 year Strong capacity for statistical data analysis.
• Intellectual curiosity and persistence to find answers.
• Advanced English.
• Ability to interact with multicultural work teams remotely.
• Interested in continuously learning and adopting new technologies/tools.
• Minimum one year of experience handling Python, knowledge of SQL.
• Intermediate level in use of Office applications (Excel, Power Point).
• Experience in large-scale sampling and/or surveys.

Additional Information

• Guarantee the quality and integrity of the data used in the analyses.
• Use statistical methodologies to analyze data.
• Innovate from a critical review of statistical designs and market needs.
• Strong capacity for statistical data analysis.
• Experience in large-scale sampling and/or surveys.
• Knowledge of Machine Learning/Neural Network