Job Overview & Purpose
The Data & AI Analyst will help Cochlear identify, analyse and solve business problems through the effective, safe and responsible use of data, analytics, automation and artificial intelligence. As an early-career member of the Analytics, Data and AI function, the role applies quantitative reasoning, analytical methods and emerging technology to explore business questions, assess data, develop insights and test potential solutions. The role works with experienced data professionals, technology teams and business stakeholders to translate problems into structured analyses, prototypes, data products or evidence-based recommendations. The role has a global and cross-functional scope, supporting initiatives that may span Cochlear's regions, functions and enterprise platforms. It contributes to Cochlear's business outcomes by improving decision-making, increasing productivity, strengthening data quality and governance, and helping teams make greater use of trusted data and responsible AI. This is a functional enablement role and does not carry direct revenue-generation accountability. It may contribute indirectly to revenue growth, cost efficiency, operational performance, innovation and customer outcomes by delivering analysis and solutions that support business decisions and process improvement.
Accountabilities
Accountability 1: Deliver data analysis and actionable insights
Accountable for producing accurate, relevant and clearly communicated analysis that helps stakeholders understand business performance, investigate problems and make evidence‐based decisions. 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.
Accountability 2: Identify and evaluate Data & AI opportunities
Accountable for helping identify business problems and opportunities that may benefit from improved data, analytics, automation, machine learning or generative AI. 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.
Accountability 3: Develop analytical prototypes and solutions
Accountable for developing fit‐for‐purpose analytical outputs and early‐stage solutions that demonstrate value and support subsequent delivery 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.
Accountability 4: Support trusted, governed and responsible use of data and AI
Accountable for ensuring that analytical work is conducted in accordance with Cochlear's applicable data governance, privacy, security, quality, responsible AI and regulatory requirements. 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.
Accountability 5: Collaborate with stakeholders and communicate technical work clearly
Accountable for building productive working relationships and making analytical findings understandable and useful to both technical and non-technical stakeholders. 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, transparent communication, effective collaboration and the practical adoption of recommendations or outputs.
Accountability 6: Build capability and continuously improve Data & AI practices
Accountable for developing personal capability while contributing reusable knowledge, improved methods and a culture of curiosity and responsible experimentation. 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.
Team Role
Individual contributor: 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.
Minimum Key Incumbent Requirements
Required Skills
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.
Desired Skills
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.
Certifications
No formal professional certification is required. Relevant entry‐level certifications in data analytics, cloud platforms, AI, data visualisation or related technologies would be advantageous but are not essential.
Education
Bachelor's degree in Mathematics, Physics, Statistics, Data Science, Computer Science, Engineering or another highly quantitative discipline.
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.
How we recognise your contribution
At Cochlear we value and welcome the unique contributions, perspectives, experiences, and backgrounds of our employees and aim to build a culture that celebrates and leverages these differences, creating a sense of belonging and enabling our people to realise their full potential. Through our internal programs and employee benefits, we aim to create an setting where our people will feel value and supported. Whether your focus is on continuous learning, professional development or simply finding an environment which enables you to thrive whilst balancing family or personal life commitments, then we have several programs in place to support you.
For more information about Life at Cochlear, visit
Our growth is creating great opportunities! Our team is expanding and we want to hire the most talented people we can. Continued success depends on it. So once you've had a chance to explore our current open positions, apply to the ones you feel suit you best and keep track of both your progress in the selection process, and new postings that might interest you!
We're the global leader in implantable hearing solutions. We have provided more than 600,000 implantable devices, helping people of all ages to lead full and active lives. We help people hear and be heard. We empower people to connect with others and live a full life. We help transform the way people understand and treat hearing loss. We innovate and bring to market a range of implantable hearing solutions that deliver a lifetime of hearing outcomes.
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📌 Data & Ai Analyst (Sydney)
🏢 C01 Cochlear Limited (Australia)
📍 Sydney