Position overview

The Data Scientist is responsible for the delivery of data science proof of concept (POC) projects, supporting their transition into production systems and ongoing performance monitoring. They work collaboratively across the organisation to support the identification and development of Artificial Intelligence (AI) products and contribute to internal and external proposals. The Data Scientist applies established data science methods across a range of domains and continues to build their technical expertise in deploying data science tools and techniques. They develop tested, version-controlled code and analytical outputs that support and enhance existing workflows, with a focus on learning and applying AI, Natural Language Processing (NLP) and machine learning techniques within ACER's assessment, analysis and reporting processes. The Data Scientist is expected to contribute to the development and maintenance of well-documented data science products and programs, working in collaboration with senior team members. In addition, they collaborate with ACER IT and internal stakeholders to support the development of statistical and algorithmic software solutions using contemporary cloud-based technologies. The Statistical Software and Analytics team and broader Data Science and Automation Program support the business to get the most value out of these tools and help shape new digital ways of working for the organisation.

Position context

The Australian Council for Educational Research (ACER) is an international, independent, not-for profit educational research and development organisation. Approximately 400 staff work for the ACER Group in Australia, India, Malaysia, the United Arab Emirates and the United Kingdom. The Measurement, Analytics and Technologies (MAT) division is a key driver of ACER's innovation in assessment science and data-driven solutions. It comprises two research programs:

Methodology & Measurement
Data Science & Automation

The Methodology & Measurement Program focuses on advancing ACER's capabilities in psychometric and statistical analysis, complex sampling, and quantitative research methods. It plays a critical role in maintaining ACER's competitive edge by ensuring methodological rigour and fostering innovation in emerging areas such as computational psychometrics. The Data Science & Automation Program is designed to modernise ACER's data infrastructure and analytical workflows. It will lead the development of algorithmic and AI-driven automation across assessment design, analysis, quality assurance, and reporting. This program will collaborate closely with subject-matter experts and ACER's IT team to build advanced statistical tools, new data products, and actionable insights. MAT supports both internal and external clients, delivering solutions that span the full learner lifecycle—from early childhood through to adult and professional education. The division's work underpins ACER's commitment to evidence-based assessment, innovation, and data-driven educational improvement. ACER is committed to the professional growth of staff throughout their employment. It encourages and supports staff in a variety of ways to actively pursue professional learning, including with reference to the ACER Leadership Development Framework. ACER encourages all staff to consider ways in which they might make a leadership contribution to ACER's work.

Job responsibilities

Design, develop and deliver tested, version-controlled software and data products, including AI, NLP and machine learning solutions for analytical and statistical applications.
Translate contemporary statistical, psychometric and machine learning research into proof-of-concept code and production-ready analytical solutions.
Work with structured and unstructured data, using advanced SQL to explore data models, extract data and maintain data quality.
Apply advanced programming skills in Python and/or R to develop, test and maintain data science models, pipelines and analytical workflows.
Develop and maintain analytic outputs and data products that support Power BI and other visualisation and reporting tools.
Collaborate with internal and external stakeholders to gather requirements, demonstrate solutions and develop bespoke analytical and statistical modelling tools.
Apply responsible AI principles, including privacy, fairness, explainability, reproducibility and model governance requirements.
Work with ACER IT to ensure security, architecture and technical standards are incorporated into analytical solutions.
Develop and maintain technical and user documentation, supporting usability testing, ongoing maintenance and continuous improvement activities.
Contribute to problem solving, operational objectives and team capability through knowledge sharing, professional development and continuous improvement initiatives

Organisational accountabilities

Proactively work towards achieving individual, team and organisational objectives while demonstrating ACER's leadership behaviours:

Developing Self – involves self-management, self-reflection and self-improvement
Embracing Change – being open to change and leading change when appropriate
Pursuing Excellence – ongoing search for new and better ways of working
Setting Directions – strategic thinking and planning for the future
Supporting Colleagues – supporting and contributing to the development of others
Working Collaboratively – building highly effective internal and external relationships

Actively work to create an equitable, fair and harmonious work environment which is free from harassment, bullying and discrimination by demonstrating respectful and courteous behaviour towards others

Proactively foster an inclusive and diverse work environment which encourages and respects different experiences and perspectives, and values diversity of thought

Comply with all occupational health and safety requirements, including following safe work practices for self and others

Work in accordance with ACER's policies and procedures

Skills, knowledge and experience

Essential

Demonstrated initiative, resilience, professionalism and a strong customer focus in a dynamic environment.
Demonstrated 3+ years' relevant professional experience in applied data science, AI, advanced analytics or a related field.
Demonstrated experience undertaking statistical or analytical software requirements gathering and translating these into operational software, workflows and automated pipelines.
Demonstrated experience applying one or more machine learning, NLP or AI techniques in operational settings, including the delivery of integrated analysis and reporting workflows.
Experience contributing in applied AI projects within enterprise, government or academic environments.
Familiarity with modern Agile delivery practices and tools (e.g. Jira, Confluence).
Familiarity with DevOps and/or MLOps practices, including experience with cloud platforms such as AWS or Azure.
Ability to clearly communicate technical and applied approaches, concepts and outcomes both verbally and in writing.
Demonstrated interpersonal skills, including the ability to build and maintain effective working relationships with internal and external stakeholders from culturally diverse backgrounds.
Demonstrated ability to work both independently and collaboratively as part of a team.
Demonstrated commitment to continuous improvement and professional development.

Desirable

Experience in delivering AI, data science, analytical products in enterprise systems.
Experience in education, assessment, public sector, or other high stakes analytical domains.
Contributions to knowledge sharing such as presentations, internal forums or publications.

Qualifications

Postgraduate qualification (Master's degree or PhD) in a relevant discipline (e.g. statistics, data science, computer science, quantitative psychology or related field), or equivalent experience. PhD preferred, or equivalent experience demonstrating advanced methodological expertise and applied delivery.

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