Senior Data Scientist

About the job You will work with a global team dedicated to the development of new methodologies for Retail Establishment Survey & other data collection processes.

We are looking for someone in our methods team to be part of these transformational initiatives to improve quality and redefine the process of RES design and Universe Estimation leveraging advanced technologies, integration of data sources, Machine Learning techniques, statistical and data analytical skills.

You should have a passion for innovation, Research & Development and challenging data opportunities!

Responsibilities Own & lead evaluating & improvising the methodologies developed to improve quality of RES Designs and transforming Universe Estimation process involving Machine Learning & Statistical techniques.

Research new methodologies, research directions and quantify their improvement Deliver methodological enhancements improving overall quality & process efficiencies.

Work closely with different teams such as technology, other Data Science teams, internal stakeholders during development & deployment of new methodologies.

Prototype as well as support pilot programs to drive innovation.

Owns and maintains Data Science global methodologies and ensures they are well documented and understood.

Asks questions to engage & motivate team on seeking further understanding of data.

Reviews the progress of projects and POCs and proposes improvements and constructive critiques.

Master’s / Doctorate Degree in Data Science, Mathematics, Statistics or Engineering degree in Computer Science, Data Science or related fields involving statistical analysis of large data sets At least 5 years’ of relevant experience Exhibits a solid understanding of FMCG Industry for specific core process and Advanced knowledge of RMS systems/products.

Experience in designing studies/sampling Comfortable designing solutions and supporting a team to execute Displays innovative thinking, data analytical skills, application of statistical techniques and encourages. experimentation in delivery of work.

Can support others to understand and apply more complicated technical principles & methodologies, creating clarity and focus for teams to deliver.

Domain expert knowledge of the following: programming, statistical analysis / machine learning/deep learning, time series, sampling Experienced in Python programming, machine learning and working with queries and large-scale databases Preferable knowledge of geospatial data and techniques Able to work in virtual environment and familiar with git/Bitbucket processes Drive to continuously learn and adopt new technologies and tools Strong communication, presentation and collaboration skills