• Serve as a primary technical field contact for internal applications support teams and as an SME in NIPT and Bioinformatics • Responsible for knowledge transfer and support for frontline staff • Deliver customer trainings and Illumina professional services as needed • Provide data analysis, logistical, and troubleshooting support for complex issues • Provide basic applications support (installation, system validation, customer training) to customers in Australia and New Zealand using Illumina's high throughput sequencing and array systems as needed • Troubleshoot issues related to user's technical skills, biochemistry/assay design, experimental design, software and instruments • Interpret customer needs and identify if the responsibility for a problem resolution falls to product management, engineering, or other company personnel • Liaise with internal teams (Product, Field and Technical support) during troubleshooting process • Act as a first point of contact within both ANZ and APJ to resolve complex NIPT applications and bioinformatics issues in the district and region, both on site and remotely • Liaise with Regional and Global Product Support teams to ensure timely communication and advice provision on current issues to field teams • Coordinate educational efforts with NIPT and Bioinformatics support teams globally • Develop and maintain positive relationships with customers • Coordinate and execute on installations including facility inspections, instrument validation, and customer training • Support sales efforts through technical presentations and customer management • Act as a key contributor of customer feedback to marketing and product development teams • Develop and improve key company processes that support our mission of building a world-class customer support organization • Mentor and coach internal support team members in area of expertise

• Deliver customer training, technical presentations, and application guidance to ensure successful use of SCIENION technologies after installation • Act as the primary scientific contact for application questions, troubleshooting, workflow optimization, and field problem-solving • Support customers and internal teams by preparing technical documentation, training materials, and maintaining accurate records of support activities • Collaborate closely with service, support, development, and commercial colleagues to convey customer feedback and enhance the customer experience

• Identify and structure a problem • Formulate hypotheses • Analyze data to validate hypotheses and provide evidence for decision-making • Make decisions with calculated risks • Formulate policies for the business • Monitor experiments, implementations, and results • Scrutinize numbers and decisions, acting as a guardian of a data-driven decision culture • Communicate findings to leadership and support different business areas in strategic decisions • Work daily on a variety of topics and with people from diverse backgrounds

• Critically evaluate ML model outputs to ensure alignment with financial theory and real-world market dynamics, while accounting for client-specific objectives, constraints, and investment frameworks. • Translate research signals into actionable investment strategies and portfolio construction frameworks. • Collaborate with ML researchers to refine models, incorporating financial domain expertise and contributing to model design where needed. • Design, prototype, and scale quantitative models using Python and Java, maintaining a high standard for code quality and modularity. • Contribute to the financial validation layer of the R&D cycle by developing and maintaining test frameworks that identify inconsistencies and support continuous model improvement. • Translate complex portfolio objectives into rigorous, testable modeling specifications that bridge the gap between investment intent and algorithmic execution. • Collaborate across technical workstreams to ensure research outputs are aligned with investment objectives and successfully integrated into production workflows.