Lead Data Scientist

Responsibilities

· Own & lead evaluating & improvising the methodologies developed to improve quality of RES Designs and transforming Universe Estimation process.

· 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 7 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

· 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 at least in one area of the following: programming, statistical analysis / machine learning/deep learning, time series, sampling

· Experienced in Python programming and working with queries and large-scale databases

· 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

Our Benefits

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