Work across all aspects of data from engineering to building sophisticated visualisations, machine learning models and experiments
Analyse and interpret large (PB-scale) volumes of transactional, operational and customer data using proprietary and open source data tools, platforms and analytical tool kits
Translate complex findings into simple visualisations and recommendations for execution by operational teams and executives
Be part of a fast-paced industry and organisation where time to market is critical
Requirements
Degree in a quantitative discipline, such as Mathematics/Statistics, Actuarial Sciences, Computer Science, Engineering, or Life Sciences
3-5 years of full-time work experience in an Analytics or Data Science role
A self-driven team player with the ability to quickly learn and apply new tools and techniques such as proprietary analytical software, data models and programming languages
A natural curiosity to identify, investigate and explain trends and patterns in data and an ability to analyse and break down complex concepts and technical findings into clear and simple language for communication
A passion for Emerging Technologies related to Blockchain, Machine Learning and AI
**Competency in two or more of the following:**
An analytical software (e.g. R, SAS)
A data visualisation tool (e.g. Qlikview, Tableau, PowerBI,)
A relational or graph database management tool (e.g. SQL, NoSQL, Neo4J)
Programming (e.g. VBA, C++, Java, Python)
Benefits
Competitive salary and company benefits
Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team)
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data analysismachine learningdata visualizationprogrammingstatistical analysisdata modelingdata interpretationtransactional data analysisoperational data analysiscustomer data analysis