You will apply you expert experience in engineering methods, deep knowledge of fundamentals, and related mechanics to design end to end machine learning solutions while contributing to overall group technology strategy.
You will work on projects that redefine the future of banking products and consumer engagement. In doing so you will bring together vast amounts of transactional data from financial sources available across the organisation and business partners to develop predictive models using a variety of methods including machine learning, statistical modelling, Natural Learning Processing etc.
In addition to modelling, your design direction will include:
-Harvest, transport, aggregate, enrich, clean, and manage data inclusive of its linage
-Recommend appropriate platform choices
-Set governance and practice standards for versioning, maintaining, monitoring, reuse and evolving solutions
As a seasoned practitioner you will have:
-Experience in designing, building, and optimizing Big Data pipelinse, architectures and working with large data sets
-Proficiency with statistics , machine learning models techniques and how to apply them to build large scale data architectures
-Experience with big data technologies
-Deep expertise in analytical tools such as, R
-Experience with scripting languages, e.g. python
-Relational databases and usage of SQL
-Expertise in DevOps, Docker, Chef, containerization, automation techniques and familiar with a Linux environment and shell scripting
-Familiar with data extract, transform and load processes with a variety of data types