Location - Australian based (Remote) with working rights
Reports To - Senior Data Science Engineer, VAPAR
About VAPAR
VAPAR is deep-tech company accelerating asset health improvements on wastewater and drainage networks. By leveraging AI and automation, we empower clients to rapidly find and fix problematic underground assets before they fail. Our solutions are used to drive efficiencies by leading UK water companies, as well as utilities in the US, Australia and New Zealand. Last year alone, VAPAR's AI technology has powered asset health investments on over 2 million metres of pipe in United Kingdom, United States, Australia and New Zealand and continues to scale globally through partnerships with Autodesk and Microsoft.
We turn visual data about every-day pipes directly into condition scores so maintenance and repairs happen faster, cheaper and more accurately.
About the role
We're looking for someone mid to senior level who is comfortable taking ownership of their role. In this role, you'll be working within our tech team on our automation technology, creating high performance models and generating insights. As the team grows, you'll have the opportunity to grow with a great team, and we'll support you with the required training to do so. We want you to become a pillar of the team and have a big impact on what we're building at VAPAR.
As a Data Engineer at VAPAR, you'll actively contribute to the development of AI-powered solutions that tackle the complex problems associated with pipe and sewer maintenance. Our company culture thrives on innovation, teamwork, respect and a relentless pursuit of excellence. While enjoying the flexibility of a fully remote position within Australia, you'll collaborate with a diverse team of professionals who share your enthusiasm for cutting-edge technology and its potential to shape a better future for infrastructure management.
Day in the life
We are seeking an experienced and motivated Data Scientist with a minimum of 3 years of experience to join our development team. The ideal candidate should be well-versed in software development principles, possess a strong foundation in Python programming, and demonstrate a proven track record in data engineering and model development. In addition to these skills, the right candidate should have a good understanding of deep learning frameworks and be well versed in libraries such as PyTorch and Tensorflow (ideally 1-2 years hands on). As a Data Scientist at VAPAR, you'll collaborate with the team to deliver high-quality software solutions that meet customer needs and drive company success.
In this role, you'll…
- Develop, test, and maintain model training, testing and inferencing code following industry best practices and coding standards.
- Conduct exploratory data analysis to identify trends, patterns, and insights.
- Extract, transform, and load data from various sources, and use SQL queries to extract insights from the data
- Collaborate with product managers and other engineers to bring together data from different sources for the purpose of data analytics and model monitoring.
- Apply your expertise with Azure to develop against cloud-based services.
- Participate in code reviews to ensure code quality, performance, and adherence to coding standards.
- Identify and troubleshoot performance issues and provide timely solutions to uphold product integrity.
- Contribute to the architecture, design, and implementation of enhancements.
- Create and maintain technical documentation, including specifications, design documents, and user guides.
- Stay updated with emerging technologies and trends in data science to drive continuous improvement.
Must-have skills
- On day one we'll expect you to have…
- Bachelor's degree in Computer Science, Data Science, Software Engineering, or a related field (or equivalent work experience).
- 2+ years of professional experience in Python software development and its libraries, especially in the context of data analysis and machine learning.
- SQL skills: You should be comfortable working with SQL to extract and manipulate data from databases.
- ETL experience: You should have some level of experience working with ETL (Extract, Transform, Load) processes and tools to manage data from different sources.
- Model monitoring experience: You should have experience monitoring the performance of machine learning models, identifying and resolving issues, and implementing solutions to ensure model accuracy.
- Product performance measurement: You should have some level of experience or knowledge in measuring and analyzing product performance metrics, including developing and maintaining internal dashboards and data visualization tools.
- Solid understanding of software development principles, algorithms, and data structures.
- Familiarity with industry standard software development methodologies, such as Agile or Scrum.
- Ability to analyse and solve complex technical problems and work independently in a remote setting.
- Excellent communication skills, both written and verbal.
- Experience with Azure and/or AWS cloud-based offerings.
Selling points
- Flexible working hours with ability to work remotely
- Work with a driven, fun and switched on team that likes to raise the bar in all that we do.
- Genuine career growth opportunities as we continue to expand!
More about VAPAR
Website: CCTV Pipe Inspection Software Powered with AI - https://vapar.co/
LinkedIn: https://www.linkedin.com/company/vapar
VAPAR was founded by Amanda Siqueira and Michelle Aguilar in 2018. As a Civil Engineer, Amanda had seen enough of the inefficiencies in the pipe condition assessment process, and teamed up with Michelle (a Mechatronic Engineer with Intelligent Systems experience) to build technology to enable pipe asset managers to revolutionise their way of working. Since then, the VAPAR team has grown and now has clients in Australia, the UK and New Zealand and continues to scale.
Pay: $120,000.00 – $150,000.00 per year
Benefits:
- Employee stock purchase plan
- Parental leave
- Referral program
- Travel reimbursement
- Work from home
Application Question(s):
- Are you located in Australia?
Experience:
- Data Engineering: 2 years (Required)
- SQL: 1 year (Preferred)
- Python: 2 years (Required)
Work Authorisation:
Work Location: Hybrid remote in Sydney NSW
