- Full Time
Data Scientist – Remote
PE Global are seeking to identify a Data Scientist to join one of our key clients – a global transportation solutions provider offering critical solutions across multiple industries including innovating sustainable temperature control transportation and storage solutions to the pharmaceutical industry as a vital enable to maintaining the quality and effectiveness of key medicines.
Role Overview / Summary:
The role will entail research, modelling behavioural data, unstructured data, applying analytical, programming, statistical and machine learning techniques, create data-driven solutions for customers, enhancing product lines and service offering alongside their Connected Solutions team/tech hub – collectively empowered to define and innovate the company’s future transport solutions, constantly evolving and embracing new technologies, best practices and new trends to ensure they are positioned to adapt quickly to global market demand and client needs and utilises IOT, Big Data to drive innovation throughout their product range across firmware, server, database, front end development and mobile apps solutions promoting collaboration between different agile development teams working remotely and when possible remote/onsite hybrid.
Currently, they have offices and tech hubs across EU, US, Latin America, Australasia. Good pkg with pension, healthcare and bonus and promote continuous learning and progression.
- Ability to research and create data driven solutions that enhance our product lines and service offerings for global customers
Knowledge in the areas of Statistical computing languages and tools, conventional languages
- Hands on experience with cloud based architectures and software stacks
- Understanding of large enterprise system architectures
- Algorithm optimisation proficiency
- Degree/Masters in Data Science, Mathematics, Physics, Relational subject
- Strong analytical skills relating to unstructured data sets
- Strong experience modelling machine and behavioural data
- Proficient with machine learning techniques
- Experience with a wide variety of statistical computer languages and data mining tools