Job description

Help shape a data-enabled future for audit. You will lead the refinement and prototyping of advanced analytics ideas that strengthen assurance, improve efficiency, and deliver clearer insights. As a Data Scientist on the Internal Audit, Data Analytics team, you will partner closely with audit stakeholders to turn promising ideas into development-ready prototypes. Working with global colleagues, you will guide concepts from early problem framing through feasibility assessment, proof-of-concept development, and hand-off to a product owner. You will combine strong leadership with deep technical expertise to help teams adopt innovative approaches to testing business and technology controls Job responsibilities • Evaluate and develop new analytics ideas, ensuring alignment with audit priorities and organizational goal • Facilitate stakeholder sessions to refine problem statements and confirm a shared understanding of the need • Define expected benefits and gather empirical evidence to support proposals and prioritization • Present findings and recommendations to decision-makers to support clear Go/No-Go outcomes • Lead feasibility work (environment setup, data acquisition, prototyping, and results review) and iterate based on learnings • Produce clear documentation and ensure effective hand-off of artifacts to the product owner for downstream delivery • Promote collaboration, critical thinking, and experimentation, and support teams in understanding data governance and required use-case approvals Required qualifications, capabilities, and skills • Demonstrated leadership and influencing skills, with the ability to gain alignment across varied stakeholder groups • Advanced knowledge of machine learning methods, deep learning frameworks, and natural language processing techniques • Strong analytical and problem-solving skills to assess feasibility and translate ideas into actionable prototypes • Excellent written and verbal communication skills, including the ability to explain complex concepts clearly • Experience managing multiple initiatives concurrently, including use of Agile delivery practices • Hands-on technical proficiency in data analysis and visualization tools • Strong documentation discipline, including the ability to produce development-ready artifacts and decision materials Preferred qualifications, capabilities, and skills • Experience building proof-of-concept prototypes and transitioning them to delivery teams through structured hand-offs • Familiarity with analytics use in audit, risk, compliance, or control testing environments • Experience facilitating working sessions with senior leaders and cross-functional teams • Proficiency with common project management tools used to track and deliver concurrent initiatives Lead data science innovation to prototype analytics that improve audit efficiency, insight, and control testing.

Requirements

Must-haves

Help shape a data-enabled future for audit. You will lead the refinement and prototyping of advanced analytics ideas that strengthen assurance, improve efficiency, and deliver clearer insights.
Evaluate and develop new analytics ideas, ensuring alignment with audit priorities and organizational goal
Facilitate stakeholder sessions to refine problem statements and confirm a shared understanding of the need
Define expected benefits and gather empirical evidence to support proposals and prioritization
Present findings and recommendations to decision-makers to support clear Go/No-Go outcomes
Lead feasibility work (environment setup, data acquisition, prototyping, and results review) and iterate based on learnings
Produce clear documentation and ensure effective hand-off of artifacts to the product owner for downstream delivery
Promote collaboration, critical thinking, and experimentation, and support teams in understanding data governance and required use-case approvals
Required qualifications, capabilities, and skills
Demonstrated leadership and influencing skills, with the ability to gain alignment across varied stakeholder groups
Advanced knowledge of machine learning methods, deep learning frameworks, and natural language processing techniques
Strong analytical and problem-solving skills to assess feasibility and translate ideas into actionable prototypes
Excellent written and verbal communication skills, including the ability to explain complex concepts clearly
Experience managing multiple initiatives concurrently, including use of Agile delivery practices
Hands-on technical proficiency in data analysis and visualization tools
Strong documentation discipline, including the ability to produce development-ready artifacts and decision materials
Experience building proof-of-concept prototypes and transitioning them to delivery teams through structured hand-offs
Familiarity with analytics use in audit, risk, compliance, or control testing environments
Experience facilitating working sessions with senior leaders and cross-functional teams
Proficiency with common project management tools used to track and deliver concurrent initiatives
Lead data science innovation to prototype analytics that improve audit efficiency, insight, and control testing.

Nice-to-haves

Preferred qualifications, capabilities, and skills

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

gomachine learningagile

Platform: oracle-cloud
Effort: medium