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About Our Client
In Bupa Group Internal Audit (GIA), we're more than auditors; we're leaders, innovators, and champions of positive change. You'll be joining a dynamic global team of over 130 dedicated professionals. We use our best-in-class expertise in internal controls to bring value to Bupa.
Job Description
You'll bring your communication, analysis, problem-solving skills and initiative to this role to:
Support the Global Head of Analytics Assurance in delivering the team's vision and development roadmap and manage the implementation of functional initiatives in the department. Empower the Internal Audit team through the development of a data analytics and reporting ecosystem. Support and deliver on data-driven audit planning including data analytics strategies to identify high-risk areas, prioritise audit activities and optimise resource allocation. Support and deliver on multiple analytics assurance activities, ensuring timely completion to a high standard in accordance with our methodology, processes and procedures. Collaborate with the Internal Audit Managers in the collection and analysis of data to deliver audit requirements, continuous auditing purposes and planning insights for reporting to key stakeholders. Build and manage relationships with stakeholders across the business outside of GIA. Deliver insightful analysis that enables audit teams to achieve their objectives. Standardise semi-structured and complex data types into consumable data models that are accessible to users in Internal Audit. Develop and present data analytic engagement reports and findings to senior management. Oversee analysts on individual audits, including allocation and review of audit work as well as day-to-day support and advice. Drive continuous improvement in GIA, your team, and your own personal performanceThe Successful Applicant
6+ years of experience in data science, AI, or related fields. Expertise in programming languages such as SQL, Python, R and visualisation tools (PowerBI, Qlik, Tableau). Experience with Natural Language Processing (NLP) libraries such as NLTK, Gensim, or spaCy. Experience with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn. Strong analytical and problem-solving abilities. Strong communication skills and confidence in written and verbal presentation to stakeholders. Bachelor's degree in computer science, Information Technology, or related field with good educational record up to degree level.