Lead Data Scientist (PROJ-4375)

Key duties and responsibilities

• Undertake analysis to define, structure and solve complex data problems including the generation and collection of data and meta-data from a variety of sources.
• Understand and utilise analytical tools including Artificial Intelligence, machine learning and predictive analytics to prioritise and solve complex problems and test models and simulations to achieve business outcomes.
• Identify and maintain test data, scenarios, hypotheses and testing plans.
• Provide advice on data generation and analysis techniques, methods applications and outcomes.
• Responsible for the ethical use of data and interpreting and complying with legislation, the Australian Signals Directorate policy and regulatory frameworks including data management requirements.
• Contribute to the management of the risks associated with the use of data including balancing security and privacy against the benefits of collecting and sharing data.
• Build and sustain effective relationships and negotiate with customers and key stakeholders to deliver tailored recommendations.
• Resolve problems using knowledge, professional judgement and initiative to identify and recommend alternative courses of action.
• Accountable for accurate and timely completion of work, sharing own expertise with others and guiding less experienced employees.
• Develop and maintain business domain knowledge, understanding of the Australian Signals Directorate data, data analysis skills and awareness emerging techniques and trends.

Technical skills

• Possesses knowledge of Machine Learning, data classification, cluster analysis, data mining, databases, visualisation.
• Possesses knowledge and experience in development languages/ technologies such as Python, ElasticSearch, Linux and Apache NiFi.

Essential criteria

• Data modelling and design: Level 4 (SFIA) Investigates enterprise data requirements where there is some complexity and ambiguity. Plans own data modelling and design activities, selecting appropriate techniques and the correct level of detail for meeting assigned objectives. Provides advice and guidance to others using the data structures and associated components.

• Data science: Level 5 (SFIA) Plans and drives all stages of the development of data science and analytics solutions. Provides expert advice to evaluate the problems to be solved and the need for data science solutions. Identifies what data sources to use or acquire. Specifies and applies appropriate data science techniques and specialised programming languages. Reviews the benefits and value of data science techniques and tools and recommends improvements. Contributes to developing policy, standards and guidelines for developing, evaluating, monitoring and deploying data science solutions.

• Data visualisation: Level 4 (SFIA) Applies a variety of visualisation techniques and designs the content and appearance of data visuals. Operationalises and automates activities for efficient and timely production of data visuals. Selects appropriate visualisation approaches from a range of applicable options. Contributes to exploration and experimentation in data visualisation.

• Programming/software development: Level 3 (SFIA) Designs, codes, verifies, tests, documents, amends and refactors moderately complex programs/scripts. Applies agreed standards and tools to achieve a well-engineered result. Monitors and reports on progress. Identifies issues related to software development activities. Proposes practical solutions to resolve issues. Collaborates in reviews of work with others as appropriate.