Data Scientist, People Analytics

About the role

Data Scientist, People Analytics (Human Resources) **Multiple Roles** **Sydney/Melbourne location** Help shape the future of workforce at CommBank through data, AI and analytics You are an inquisitive and experienced data science professional with a genuine passion for solving complex workforce problems through data, analytics, machine learning and AI. We are a value-driven team of analytical experts who use data science, advanced analytics and emerging technologies to generate trusted insights, deliver scalable solutions and enhance employee experiences. Together, we harness analytics, Generative AI, machine learning and human-centred thinking to help CBA better understand its workforce, anticipate future capability needs and make evidence-based decisions that support our people, customers and communities. Do work that matters: People are central to the Group's strategy. Human Resources partners with our Business Units to build a vibrant, customer-focused and high-integrity culture, supporting our people across every stage of the employee lifecycle - from talent acquisition, leadership development and learning, through to internal mobility, employee relations, remuneration and benefits. As the nature of work continues to evolve, advances in AI, automation, digital transformation and skills-based workforce planning are reshaping how organisations think about capability, productivity, employee experience and workforce resilience. At CBA, People Analytics helps leaders understand these shifts, anticipate future workforce needs and make informed decisions that support our people, customers and communities. In this role You will contribute to the development of data science and AI solutions that help improve workforce decision-making and employee experiences. You will analyse complex workforce datasets, apply appropriate modelling and statistical techniques, and support the build, evaluation and deployment of ML and GenAI solutions . Working as part of the People Analytics Chapter, you will collaborate with data scientists, data engineers, platform teams and stakeholders to deliver solutions that are accurate, well-governed and aligned to business outcomes. Key responsibilities include Partner with HR, business stakeholders and team members to understand workforce challenges and translate them into analytical, ML and GenAI opportunities. Develop data science and AI solutions that support workforce priorities, including skills, capability, workforce planning, employee experience, mobility and organisational effectiveness. Analyse large and complex workforce datasets, applying data preparation, feature engineering, modelling, validation and interpretation techniques. Build, test and evaluate machine learning and Generative AI models using appropriate statistical methods, performance metrics and responsible AI practices. Support the deployment, monitoring and ongoing improvement of ML models and analytical solutions in collaboration with senior data scientists and MLOps teams. Use cloud computing services, data science tooling and software engineering practices to help develop scalable and maintainable analytical assets. Use Generative AI tools to assist with coding, analysis, prompt development, summarisation and integration of AI-generated outputs with human-led judgement. Translate analytical outputs into clear narratives, dashboards, reports and recommendations for HR leaders, Centres of Excellence and business stakeholders. Apply ethical, privacy-aware and explainable AI practices when working with sensitive people data. Contribute to reusable code, documentation, analytical frameworks and knowledge-sharing across the People Analytics Chapter. Provide guidance and support to junior data scientists and analysts, helping uplift data science and AI capability across the team. We're interested in hearing from people who: Have strong foundations in statistical modelling, machine learning, Generative AI and applied data science. Are confident using Python or R, SQL and modern data science workflows to work with large and complex datasets. Have familiarity with the AWS technology stack and cloud-based data science workflows, including services such as S3, SageMaker, Bedrock, Lambda, Glue or related analytics and ML tooling. Have experience building, evaluating or integrating machine learning models, LLMs, Generative AI APIs or AI-enabled solutions. Can prepare, clean and transform complex data for modelling, analysis and insight generation. Understand responsible AI, privacy, explainability and ethical use of people data. Can translate business questions into clear analytical approaches and practical solutions. Are strong communicators who can explain complex findings to both technical and non-technical audiences. Have experience with BI and visualisation tools such as Tableau or Power BI. Bring curiosity about the future of work, workforce transformation and the role of AI in shaping employee experiences

Your Match

How well this role fits your profile.

Company Intel

What employees say

Worked at cba? Share your experience