Description of Business Unit:
Group Internal Audit (GIA) is on a journey towards a digital future, where automation, technology and data will act as key enablers to both what we do, and how we do it. The Data Solutions & Analytics function within GIA is responsible for the development and execution of GIA's 'Digital & Data' strategy and digital transformation roadmap (DTR), to enable GIA to embed technology, data science and automation techniques at the heart of its operating model. The Data Solutions & Analytics function has responsibility for:
Digital Strategy & Transformation Plan - development and execution of the GIA 'Digital & Data' strategy and transformation roadmap, based on the departments needs and desired target state.
Leveraging Data as an Asset - design, development and implementation of data science products to extract value from internal and external data sources allowing GIA to realise value and insights from data.
Developing 'Smart Processes' - re-engineering of existing processes leveraging machine learning and robotic process automation techniques to maximise the simplicity and efficiency of GIA's processes.
Setting our Tools & Technology Strategy -understanding GIA's technology and tooling needs, and defining and executing a comprehensive technology strategy to get us to our future state technology blueprint.
Enhancing our 'Digital & Data' Capability - development and execution of a multi-year training programme to enhance GIA 'Digital & Data' capabilities.
The role holder will contribute towards GIA's multi-year digital transformation strategy, through the development of multi-component data science solutions (e.g. supervised/unsupervised machine learning, natural language processing, stochastic modelling, descriptive analysis and graph analytics), creation and embedding of 'smart processes' and input into GIA's technology strategy and implementation plan. The role holder will also be responsible for the rollout of key capability and training initiatives across the division, utilising Agile principles and methodologies, designed to increase our overall level of digital and data capability across GIA.
Purpose of the Role:
This is a cross functional individual contributor role to develop complex, multi-component data science solutions to realise value from both the Group's and external data. You will also have the opportunity to input into key 'Digital & Data' strategy initiatives, including the technology strategy, development of 'smart processes' across GIA and design and implementation of training and capability initiatives as part of the wider 'Digital & Data' capability programme. You will have an opportunity to partner with the business on a wide range of projects, collaborating on new ways of working and proposing new methodologies and approaches. You will contribute more broadly to the achievement of Group Internal Audit strategic plans and priorities.
Manage the development of complex multi-component analytical solutions (including natural language processes/generation, classification and regression models and unsupervised machine learning solutions e.g. anomaly detection, clustering), from initial requirements workshops through to embedding the solution in the day to day operations of the business.
Manage sophisticated research project and analysis for senior management to drive business insights and proactive risk management across the Group.
Lead innovation projects across the function, utilising data science techniques and methodologies to inform decisions to drive enhanced risk management and insight across the Group.
Contribute towards the 'Digital & Data' strategy (and underpinning initiatives) and the wider Data Solutions & Analytics function through the identification of new value add data exploitation and continuous improvement opportunities.
Design, development and implementation of insight and management information visualisation solutions to present data driven insights to senior management within GIA, and across the Group.
Promote awareness of data science, emerging industry trends (incl. regulation) and a digital future across Group Internal Audit.
Collaborate cross-functionally (with other teams within Group Internal Audit, and across the wider Group) to refine recommendations and develop next best action plans for risk management.
Contribute to a creative culture centred on an agile environment, value prioritisation and design thinking.
What is the Opportunity?
The successful applicant will have the opportunity to help drive the execution of GIA's multi-year 'Digital and Data' strategy, to help GIA achieve its desire to be data led, technology enabled, leveraging automation techniques to optimise how we work and enhancing and augmenting our 'Digital & Data' capabilities across the function.
Third Level qualification, in computational science, computer science, mathematics, statistics or another discipline including a significant quantitative element.
Essential Skills & Experience:
Significant demonstrable experience in developing and implementing business focussed data science solutions, translating the needs of the business into a scalable, fit for purpose solution for stakeholders.
Comprehensive understanding of the methodologies underpinning machine learning and modelling techniques such as logistic regression, decision trees, neural networks, graph analytics, density based clustering and stochastic techniques etc.
Demonstrable experience in applying data science and statistical techniques to test complex hypotheses and perform 'deep dive' analysis across a wide variety of functional domains.
Demonstrable experience in leveraging SQL and Python/R to acquire, transform and extract insights from large scale complex datasets.
Demonstrable experience in developing and validating machine learning models Python, R, pySpark, sparkR or Scala.
Strong attention to detail and high levels of accuracy and a strong team ethic and flexible approach in order to meet challenging objectives and deadlines.
Excellent time management and organisational skills with the ability to work on own initiative.
High level of discretion, capable of dealing with highly confidential and sensitive information.
Desirable Qualifications, Skills & Experience:
Knowledge of the Cloudera Hadoop platform, and associated analytical tools (i.e. pySpark).
Experience in leveraging machine learning and robotic process automation techniques to re-engineer and optimise business processes would be advantageous.
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