Quality Engineer - Analytics | Canberra, ACT
|Position Type:||Full Time|
|Attachments:|| Company brouchure.pdf (PDF, 575KB)
|Application Close Date:||22-Dec-2021|
Seeing Machines is an Australian success story and a world leader in human-machine interaction and an industry leader in the artificial intelligence (AI) technologies which enable machines to see, understand and assist the people who are using them. Our technology drives a safer world.
About the opportunity
The Quality Engineer – Analytics is responsible for Identifying, designing, and implementing internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data' technologies.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
- Work with stakeholders Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Create data tools for analytics and Quality team members that assist them in building and optimizing our product into an innovative industry leader.
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Developing and implementing quality standards.
- Developing and implementing quality control systems.
- Monitoring and analysing quality performance key metrics.
- Inspecting and testing materials, equipment, processes, and products to ensure quality specifications are met.
- Collaborating with operations managers to develop and implement controls and improvements.
- Ensuring that workflows, processes, and products comply with safety regulations.
- Investigating and troubleshooting product or production issues using quality methodologies such as 8D, FTA, and 5-Why Analysis.
- Developing corrective actions, solutions, and improvements in accordance with the 8D methodology.
- Reviewing codes, specifications, and processes in accordance with ASPICE.
- Operational Efficiency Improvement
You will have demonstrated experience in a similar role with a;
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Experience building and optimizing ‘big data' data pipelines, architectures, and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
- A successful history of manipulating, processing, and extracting value from large, disconnected datasets.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data' data stores.
- Strong project management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Degree in software engineering, electronics engineering, or Analytics.
- ASPICE / IATF 16949 experience / certification preferred.
- 2+ years of experience in quality engineering, quality assurance, or a similar role.
- Experience coding and using QA software tools and processes.
How to apply
To apply, please upload your current resume and cover letter outlining your interest in the role. If you are successful for this opportunity a police check is required.
About Seeing Machines
Seeing Machines is a world leader in driver-machine interaction. We harness human factors science to create artificial intelligence (AI) technology that observes the driver's attention – reliably, unobtrusively, and in real time – and intervenes seamlessly when necessary.
Specialised computer vision algorithms underpin Seeing Machines' core camera-based driver monitoring technology. Algorithms allow us to precisely track eye gaze, head position and pupil size while our state-of-the-art AI technology analyses the data to quickly and accurately detect driver drowsiness, distraction and microsleep levels. We work with some of the world's leading brands to deliver this technology, helping keep drivers and operators engaged across commercial transport and logistics, automotive, aviation, rail and mining industries.
In automotive, we enable safer Automated Driving (AD) solutions and Advanced Driver Assistance Systems (ADAS) – including the world first camera-based hands-free driving feature, GM Super Cruise. In aviation, our advanced gaze tracking technology understands how pilots interact and monitor instruments – leading to better training and safer operations.
For commercial transport and fleet operators, the Seeing Machines retrofit driver monitoring technology provides real-time intervention for drivers to mitigate the risks associated with driver fatigue and distraction.
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