Senior Data Scientist

The Senior Data Scientist / Modelling role is responsible for designing, developing and maintaining Modelling for non-coop retailers.

Data Science oversee universe studies, set up the extrapolation for Retail Panels, select and design modelling technics for non-coop retailers, and support 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.

1. Modelling

Modelling requires general knowledge of Retail Panel production processes and methods. 3 topics are important to deeply understand

Universe Studies

• Methods and Data sources for universe studies, in collaboration with Data Science leads for the workstream.

As part of modelling, knowledge of the non-coop retailers can be gained from standard universe studies, but if it’s not possible or not sufficient, additional knowledge is required, feasibility and relevance must be assessed.

Extrapolation

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

This role is ideal for individuals with a keen eye for detail and a passion for data and data science. If you enjoy working in a dynamic environment and have the skills listed above, we encourage you to apply for the Data Scientist position.

Responsibilities

Select the modelling method of non-coop retailer modelling: via extrapolation, via basic modelling or via rawdata modelling.; 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, need to develop new components.; Design the solution, test the development, review the quality once implemented, review every year the relevancy of the solution.; Once implemented, assess the feasibility to handover to Operation for ongoing maintenance and execution. Otherwise, define the process for execution by Data Science team.; Support Commercial teams and Client Operation to explain the methodology of Rawdata modelling.; Knowledge; Business knowledge regarding channel definitions, samples design, client’s usage of Retail Panel; Participate to Data Science global projects, in close collaboration with the Research team

Requirements

Proficiency in statistical modeling and data analysis.; Strong quality orientation and solution driven.; Strong analytical and problem-solving skills.; 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.; Extensive experience of working in an international environment; Strong command of the English language

Benefits

Flexible working environment; Volunteer time off; LinkedIn Learning; Employee-Assistance-Program (EAP)