Lead Data Analyst / Performance Validation Engineer | Canberra, ACT
|Position Type:||Full Time|
|Attachments:||No File Attached|
|Application Close Date:||27-Apr-2018|
Our Data & Validation Group collects and manages critical validation and algorithm training datasets and applies their statistical analysis expertise to algorithm validation. The team acts as an internal service division and provides critical assistance to the Research & Development team and other engineering groups.
This is a genuinely stimulating and challenging opportunity to work on exciting cutting edge Big Data projects.
The Lead Data Analyst reports directly to the Director, Data and Validation and is responsible for delivering a performance reporting framework capable to meet the requirements of the Engineering, Product and Technical Sales teams.
This will require leading the performance analysis and reporting of our Driver Monitoring algorithms and systems. This will involve:
- Designing performance metrics that best characterise the algorithm, system and product performance against requirements
- Develop and maintaining performance analysis tools to generate quantitative performance metrics
- Applying relevant statistical analysis to analyse and interpret performance data
- Reporting on performance metrics, and in particular, contextualise, translate and communicate product performance to end users
- Guiding technical development across the algorithm performance team to deliver continual algorithm / system performance feedback
- Analysing customer requirements, in collaboration with Product Development Leads (e.g. Automotive OEM Programs) then translating those requirements into performance metrics and implementation
The successful applicant will have tertiary qualifications in data analytics, data science, software/systems engineering, applied statistics, mathematics or a similar quantitative discipline with strong equivalent industry experience in:
- Algorithm / product performance testing, preferably in the Computer Vision domain
- Extracting information from a wide variety of sources including quantitative, qualitative and big data sources
- Strong experience in quantitative methods of data analysis
- Strong fundamental knowledge of applied statistics
- Strong experience driving collaboration amongst Engineering teams
- Hands-on proficiency with full data analysis stack (e.g. Python numerical analysis and visualization stack, R)
- Experience in database architectures – SQL & NoSQL, map reduce paradigm, C++, C#, .NET
- Computer vision algorithms, and large video data processing
- Distributed computing such as PySpark and Dask
- Machine learning and AI frameworks
- Cloud based frameworks and services (AWS)
To apply for this role, please include an updated resume and a cover letter outlining briefly the qualifications, skills and experience that you would bring to the role.