Summary

Responsibilities

1. Work across all aspects of data from engineering to building sophisticated visualisations, machine learning models and experiments
2. Analyze and interpret large (PB-scale) volumes of transactional, operational and customer data using proprietary and open source data tools, platforms and analytical tool kits
3. Translate complex findings into simple visualisations and recommendations for execution by operational teams and executives
4. Be part of a fast-paced industry and organisation where time to market is critical

Requirements

1. Degree in a quantitative discipline, such as Mathematics/Statistics, Actuarial Sciences, Computer Science, Engineering, or Life Sciences
2. 3-5 years of full-time work experience in an Analytics or Data Science role
3. 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
4. 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
5. A passion for Emerging Technologies related to Blockchain, Machine Learning and AI

Competency in two or more of the following:

1. An analytical software (e.g. R, SAS)
2. A data visualisation tool (e.g. Qlikview, Tableau, PowerBI,)
3. A relational or graph database management tool (e.g. SQL, NoSQL, Neo4J)
4. Programming (e.g. VBA, C++, Java, Python)

Skills

• Analytical Thinking
• C++
• Communications Skills
• Development
• Java
• Machine Learning
• Python
• Team Collaboration