Position overview

The Senior Data Scientist is responsible for the delivery of data science proof of concept projects (POC), their transition into production systems, and monitoring their performance. They collaborate within the organisation to identify & define new Artificial Intelligence (AI) products, support internal/external proposals, and mentor junior staff in their professional development journey.

The Senior Data Scientist has extensive experience in multiple data science domains, expertise deploying data science tools and techniques, and developing tested, version-controlled software products that enhance and automate analytical workflows. An additional focus will be on accelerating the integration of AI, Natural Language Processing (NLP) and machine learning into ACER's broader assessment design, analysis and reporting processes and products.

The Senior Data Scientist is expected to oversee development and maintenance of well-documented data science products and programs developed by the team. In addition, they work collaboratively with ACER IT to define cutting-edge statistical and algorithmic software solutions using cloud-based web-stack 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

• Identify and address analytic and statistical problems through the design, development and delivery of tested, version-controlled software and data products, including the application of AI and NLP techniques.
• Translate contemporary statistical, psychometric and machine learning research into proof-of-concept code and validated, production-ready analytical solutions.
• Develop, maintain, and extend analysis software and models in collaboration with the Methodology and Measurement Program and ACER IT, ensuring alignment with technical standards.
• Work with structured and unstructured data from multiple systems, using advanced SQL to explore data models, extract data and assure data quality.
• Demonstrate high proficiency in Python and/or R, including the effective use of common data science and machine learning libraries.
• Develop analytic outputs and data products to support Power BI and other visualisation or reporting tools.
• Work closely with internal and external stakeholders to gather requirements, design solutions and deliver high-quality bespoke analytic and statistical modelling tools.
• Apply responsible AI principles, including privacy, fairness, explainability and reproducibility, and contribute to model governance activities.
• Collaborate with ACER IT to ensure corporate security, architecture and technical standards are integrated into all analytic solutions.
• Produce and oversee clear technical and user documentation and dissemination materials, incorporating feedback from usability testing and supporting ongoing maintenance and testing practices.
• Identify and implement operational objectives, aligning these with appropriate software frameworks, languages and methodologies.
• Lead, develop and coach staff to support high individual and team performance and build ACER's capability in modern analytic methods.
• Contribute to continuous improvement activities that enhance research quality, operational outcomes and analytics capability across ACER.

Decision Making Authority

The Senior Data Scientist does not typically hold ongoing people management accountability but may provide project-based leadership, guidance, or oversight to project team members when acting in a Project Director capacity. Decisions involving the commitment of significant resources or funding, and matters relating to staff or client relationships, are made in consultation with the relevant Project Director and/or the Research Director, Data Science and Automation.

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 and identifying, assessing, and mitigating psychosocial risks
• Comply with all information security requirements, including completing regular security training and abiding by the standards and procedures laid out in ACER's Information Security Management System
• 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 5+ 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 leading applied AI projects within enterprise, government or academic environments.
• Experience coaching junior staff, delivering capability uplift, and embedding data science products into business workflows.
• 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.
• High-level organisational and project delivery skills, with demonstrated experience planning and delivering projects on time, on budget and within scope, while managing competing priorities.
• 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.