Did you know?

The mission of the Australian Federal Police is to provide dynamic and effective law enforcement to the people of Australia. It provides policing throughout Australia in relation to the prevention and detection of crimes against the Commonwealth, its laws and integrity, and community police services to the Community of the ACT.

Working for the AFP provides you with a diverse and rewarding career. Whether you immerse yourself in a position on the frontline, or provide critical operational or professional support, the work you do makes a big impact on the people of Australia.

We recognise your contribution to our workforce and offer generous remuneration and conditions including:

• Six weeks (30 days) of paid annual leave per year + additional paid Christmas stand down
• 4 extra days of mandatory rest leave per year
• 18 days of paid personal leave per year
• Generous superannuation of 15.4%
• 18 weeks paid Parental Leave for Primary Caregiver (and 11 weeks for Secondary Caregiver) + additional unpaid leave entitlements for up until 24 months from the child’s date of birth or placement
• Generous salaries and incremental salary progression governed by the AFP Enterprise Agreement
• Flexible and hybrid working arrangement that provides work/life balance
• Health & wellbeing services – with a focus on early intervention, education and prevention
• Access to ongoing training and professional development opportunities

What is the role?

The Data Enrichment and Enterprise Prototyping (DEEP) section, part of the Chief Information Officer Command, is responsible for providing enterprise data enrichment services to support the broader AFP. In a rapidly evolving technology landscape, the DEEP section provides tools to manage, triage and transform large volumes of data to support the efficient and timely analysis and review of material to meet AFP operational needs. In addition to providing enterprise data enrichment services, the DEEP team is also responsible for trialling and prototyping new capabilities in order to position the AFP to take advantage of new advances in technology.

We are seeking a highly motivated and organised individual who can work effectively under limited direction to:

• Provide subject matter expertise in the Data Science and Artificial Intelligence disciplines.
• Provide expert advice to evaluate the problems to be solved and the need for data science solutions.
• Identify and justify what data sources to use or acquire.
• Specify and apply appropriate data science techniques and specialised programming languages.
• Critically evaluate and review the benefits and value of data science techniques and tools developed across the AFP and recommends enhancements that support operational effectiveness.
• Work in cross-functional environments to co-develop technical AI and Data Science standards, policies and guidelines, and clearly defined roles and responsibilities that bring the AI lifecycle to life, embedding best practices for human-on-the-loop and human-in-the-loop oversight.
• Ensures alignment with and compliance to external AI safety standards and regulatory policies.

As a Technical Specialist in the AFP you will ensure the achievement of outcomes are in accordance with the regulatory framework, the AFP Code of Conduct and the AFP Governance Instruments. It is expected that the successful applicant will deliver on the core responsibilities and meet any requirements of the position as outlined below.

Technical Specialists provide expert consultancy within their area of expertise to develop and promote technical solutions which support the business requirements of the AFP. A Technical Specialist role does not hold any leadership or financial delegation.

What will you do?

As a Data Scientist your responsibilities include, but not limited to:

• integrating methods from mathematics, statistics and probability modelling using specialised programming languages, tools and techniques
• sourcing and preparing data for analysis
• identifying, validating and exploiting internal and external data sets generated from a diverse range of processes
• developing forward-looking, predictive, real-time, model-based insights to create value and drive effective decision-making
• finding, selecting, acquiring and ingesting data sources
• integrating and cleansing data to make it fit for purpose
• developing hypotheses and exploring data using models and analytics sandboxes
• refining requirements, validating, training and evolving models over time to discover deeper insights, make predictions or generate recommendations
• using advanced analytic techniques including, but not limited to data/text mining, machine learning, pattern matching, forecasting, visualisation, semantic analysis, sentiment analysis, network and cluster analysis, multivariate statistics, graph analysis, simulation, complex event processing and neural networks.

As a Product Owner your responsibilities include, but not limited to:

• drive the development and application of data science solutions for the business and enterprise
• overseeing all stages of model development and product ownership, using an Agile way of working and associated ceremonies
• plan, coordinate and develop cutting edge data science models and solutions
• maintain and enhance existing models to ensure optimal performance
• apply expertise to drive business growth through data-driven insights
• own and deliver data science products that meet business needs.

Essential Requirements

• You must be an Australian Citizen at the time of application.
• A Negative Vetting 1 (Secret) security clearance or the ability to obtain one.
• Has contemporary knowledge and experience relevant to the role.
• Minimum of 5 years’ experience in a like or related field.

Technical skills

• Programming Languages: Proficiency in programming is crucial for data manipulation, algorithm implementation, and automation. The most important languages are:
• Python: Widely considered the most popular language for data science due to its versatility, easy-to-learn syntax, and extensive libraries (e.g., NumPy, Pandas, scikit-learn).
• R: An open-source language primarily used for statistical computing and data visualization.
• SQL (Structured Query Language): Essential for managing and querying relational databases to extract and manipulate data.
• Statistics and Mathematics: A strong foundation in these areas is fundamental for accurate data analysis and model development. Key concepts include:
• Probability and Statistics: Hypothesis testing, regression analysis, Bayesian inference, and different statistical distributions.
• Mathematics: Linear algebra, calculus, and discrete mathematics are vital for understanding and developing machine learning algorithms.
• Machine Learning and Deep Learning: Data scientists must have a firm grasp of machine learning fundamentals, including:
• Supervised and Unsupervised Learning: Understanding the differences between these approaches.
• Model Selection and Evaluation: Knowing how to train, test, and evaluate models, and being aware of concepts like overfitting and the bias-variance trade-off.
• Algorithms: Knowledge of various algorithms and their strengths and weaknesses.
• Data Wrangling and Visualization:
• Data Wrangling: The ability to clean, structure, and enrich raw, incomplete, or unstructured data to make it ready for analysis.
• Data Visualization: Proficiency in creating compelling charts, graphs, and visualizations to communicate findings to both technical and non-technical stakeholders.
• Big Data Technologies: Familiarity with tools and technologies for processing and analysing large datasets efficiently, which may include cloud-based platforms and frameworks.

Non-technical (soft) skills

• Communication and Storytelling: The ability to translate complex data findings into clear, concise, and actionable insights for business leaders and stakeholders.
• Problem-Solving: Data scientists must be able to define a business problem, determine the right analytical approach, and apply their skills to find a solution.
• Business Acumen: Understanding the industry and the business context is crucial for ensuring that the data analysis is relevant and provides real value to the agency.
• Curiosity and Lifelong Learning: The field of data science is constantly evolving. A natural curiosity and a commitment to continuous learning are vital for staying current with new technologies and methodologies.
• Awareness of the ethical implications of data and AI, including bias, fairness, and privacy.

Desirable Requirements

The following skills and/or experience would be highly regarded:

• Bachelor's degree in Computer Science, Mathematics or Statistics and/or relevant industry experience and certification.
• Experience with major cloud providers like AWS (Amazon Web Services), Google Cloud Platform (GCP), or Microsoft Azure.
• Proficiency with Git for collaborating with other developers and managing code.
• Knowledge of A/B testing and other experimental methodologies to validate hypotheses.

Additional Information

• When applying you will be asked to nominate your preferred band level, however final determination of the band level you are found suitable for is at the discretion of the panel.
• This position has been advertised in all Australian capital cities. Although the position is generally based in Canberra/Sydney, opportunities to work remotely, or from another AFP office in Australia will be considered. A successful applicant located outside the Canberra/Sydney area will be required to travel up to 4 times per year to attend team events.
• This role is an AFP Technical Specialist Level 1 and Technical Specialist Level 2.

Commitment to Diversity & Inclusion

At the AFP we value the different perspectives, approaches and lived experiences of our people, and recognise that our collective intelligence and diversity is what makes us stronger. As such, we encourage applications from people from all walks of life, including people from culturally and linguistically diverse backgrounds, First Nations people, women, the LGBTQIA+ community and people with disability.

Contact Officer: Colin Chang,

Contact Officer Phone: (02) 5126 3199, ​

Contact Officer Email: [email protected]