Cochlear is a global leader in implantable hearing solutions dedicated to helping people with hearing loss experience a world full of sound. The Data & AI Analyst will use data analysis, analytics, automation and artificial intelligence to solve business problems, develop insights and prototypes, support responsible data use, and improve decision-making across the organization.
Gather, clean, transform and analyse data using approved Cochlear data sources, analytical environments and tools
Apply statistical, mathematical and exploratory analytical techniques to identify patterns, trends, relationships, anomalies and potential drivers of business outcomes
Develop reports, visualisations, analytical models and concise recommendations appropriate to the intended audience
Validate data, analytical assumptions and results with data owners, subject matter experts and experienced team members
Clearly document data sources, methods, assumptions, limitations and conclusions so that work is transparent and reproducible
Success will be measured by the accuracy, usefulness, clarity and timely delivery of analysis, and by the extent to which it enables better-informed business decisions
Engage with business stakeholders to understand their problems, desired outcomes, current processes and decision-making needs
Translate broad or ambiguous problems into structured questions, hypotheses, measurable outcomes and analytical work plans
Assess the availability, suitability, quality, sensitivity and limitations of data required to address an opportunity
Undertake exploratory analysis and develop early-stage proofs of concept or prototypes where appropriate
Contribute to opportunity assessments and business cases by documenting expected value, feasibility, dependencies, risks and recommended next steps
Consult with business subject matter experts, data professionals, architects, engineers, security, privacy, quality and other relevant stakeholders
Success will be demonstrated through a well-supported pipeline of practical opportunities and evidence-based recommendations that enable informed investment or prioritisation decisions
Develop exploratory models, algorithms, dashboards, automations, data products or AI prototypes using approved tools and environments
Apply appropriate software development and analytical practices, including version control, testing, peer review and technical documentation
Evaluate solution performance against agreed measures and communicate where results, data or assumptions limit the solution’s use
Work with data engineering, platform, architecture and business teams to ensure that prototypes can be understood, assessed and, where appropriate, transitioned into supported solutions
Operate primarily within Cochlear’s existing delivery, data governance, quality, security and technology processes, while contributing ideas for new methods and improved ways of working
The most complex aspect of the role is likely to be converting an ambiguous business question into a technically sound and practical solution when data is incomplete, inconsistent or distributed across multiple systems
Success will be measured by the quality, repeatability and practical relevance of prototypes, rather than the volume of prototypes produced
Use data only through authorised systems, approved access arrangements and agreed business purposes
Assess and document relevant data quality, privacy, security, bias, ethical, intellectual property and model risks
Protect confidential, personal, commercially sensitive and regulated information throughout the analytical lifecycle
Follow required review, validation and approval processes before analytical outputs or AI-enabled solutions are used for business decision-making
Escalate data issues, unexpected model behaviour, potential control failures or inappropriate uses of data and AI to the relevant manager or accountable owner
Maintain sufficient records to support review, traceability, reproducibility and audit where required
Consult with data owners, data governance specialists, security, privacy, quality, regulatory and technical experts according to the nature and risk of the work
Success will be demonstrated by compliant, well-documented delivery with risks identified early and no avoidable misuse or inappropriate disclosure of information
Work collaboratively with colleagues across business functions, regions and technical disciplines to understand needs and deliver agreed outcomes
Participate in discovery sessions, workshops, working groups, project meetings and peer reviews
Explain analytical approaches, technical concepts, uncertainties and limitations in clear language appropriate to the audience
Present findings through concise written reports, visualisations, demonstrations and verbal briefings
Seek feedback early, respond constructively and adapt analysis when new evidence or stakeholder needs emerge
Manage agreed tasks and priorities transparently, raising dependencies or delivery risks promptly
Success will be indicated by trusted stakeholder relationships, clear communication, effective collaboration and the practical adoption of recommendations or outputs
Develop practical knowledge of Cochlear’s business, data, systems, analytical platforms and applicable governance requirements
Maintain and expand technical capability in data analysis, statistics, visualisation, programming, machine learning and responsible AI
Share useful code, templates, analytical methods, documentation and lessons learned with colleagues
Contribute ideas that improve analytical quality, efficiency, repeatability and stakeholder experience
Participate in communities of practice, demonstrations, training activities and peer learning
Seek coaching, technical review and feedback from experienced practitioners, particularly where the work is novel, complex or higher risk
Success will be measured through growing independence, improved technical and business capability, reusable contributions and demonstrable continuous improvement
Follow relevant quality procedures to deliver quality products and services and identify and support the implementation of continuous improvement. Undertake additional quality responsibilities (e.g., audit) when appropriately trained to undertake these responsibilities
Contribute ideas on systems and process methods to improve deliverables
Work safely, complying with all safety procedures, rules, and instructions; and reporting workplace hazards, incidents, or injuries to manager
Qualification
Required
**Quantitative analysis and problem-solving:** Strong foundation in mathematical, statistical and scientific reasoning, with the ability to structure ambiguous problems and evaluate evidence objectively
**Data analysis and programming:** Foundational ability to use Python, R, SQL or comparable analytical tools to prepare, analyse and interpret data
**Data communication and visualisation:** Ability to explain technical findings clearly through written summaries, charts, presentations and visualisations for non-technical audiences
**Data quality and analytical rigour:** Ability to examine data critically, identify quality issues, test assumptions, validate results and document methods and limitations
**Collaboration and learning agility:** Ability to work constructively with business and technical stakeholders, seek feedback and quickly develop knowledge of new business domains, tools and technologies
Bachelor's degree in Mathematics, Physics, Statistics, Data Science, Computer Science, Engineering or another highly quantitative discipline
Preferred
Experience applying statistics, numerical methods, optimisation, simulation, experimental design or mathematical modelling to practical problems
Familiarity with data visualisation or business intelligence tools such as Power BI, Tableau or equivalent
Exposure to machine learning, generative AI, natural language processing, automation or optimisation techniques
Familiarity with cloud data platforms, data engineering concepts, APIs, Git or modern software development practices
Experience completing a university, research, internship or industry project involving real-world datasets and communicating findings to others
Relevant entry-level certifications in data analytics, cloud platforms, AI, data visualisation or related technologies would be advantageous but are not essential
Honours, postgraduate study or substantial university project work in applied mathematics, physics, statistics, data science, machine learning or a related discipline is desirable but not required
Benefit
Continuous learning programs
Professional development programs
Programs that support balancing family or personal life commitments
Cochlear is a global expert in implantable hearing solutions.
