Senior/Principal Data Scientist

Nearmap is unique. An Australian global technology company with incredible people.

At Nearmap, we have tens of petabytes of high-quality aerial imagery (covering half a million square kilometres a year at 5-7cm resolution, and regularly captured imagery back to 2009). We produce automated 3D models of entire cities, and have recently launched our new product, Nearmap AI, which turns our visual content into semantic information to power decisions in a wide range of organisations. As a publicly listed company focussed on growth, we have both the resources to allow you to succeed in your role, and the agility (thanks to cloud-based infrastructure) to rapidly take advantage of the latest developments in the field. Nearmap is continually evolving, and you’ll need to thrive in a fast-paced environment that changes rapidly.

We are recruiting for a highly skilled Data Scientist to join the AI Systems group. You will be designing, building, and operating machine learning systems that take petabytes of data to transform imagery to insight. Our technology stack is based on the python scientific libraries and traverses deep learning technology such as Tensorflow and Pytorch, cloud native technology such as Kubernetes, Kubeflow and Kafka, and GIS tools such as the Shapely and GeoPandas libraries. We are committed to software best practices including infrastructure as code, GitOps, CI/CD, and as much automation as makes sense.

You will work with an incredibly passionate and talented team of Data Scientists, Machine Learning Engineers and Data Engineers. You will design novel deep learning architectures that leverage our rich data set, multiple dates of high-resolution imagery, multi-angle source imagery and 3D textured mesh. You will be responsible for coming up with these novel architectures, designing training and evaluation methodologies, and producing the production deep learning models that are run at scale on our data. As well as multiple data sources, we ensure our models are fit for purpose within multiple geographies, and can efficiently predict on a large and growing taxonomy of labels - we use the same models to recognise objects as diverse as power poles, and large commercial and industrial buildings.

The data sets used for training the AI models are inhouse products. You will be responsible for enriching these data sets and designing efficient sampling and labelling strategies.

Experience

We are looking for highly skilled and experienced data scientist at Senior or Principal level with extensive industry experience and a track record of R&D achievements. Experience with designing and training custom artificial neural networks and deploying ML models to product is essential.

Skills

We are after an exceptional candidate, who has real world experience but is still eager to innovate and learn.

Essential:

• Programming/Tech Environments: Ability to code in scientific python, using a Linux environment, and git for source control. Commitment to software engineering principles, a keen eye for clean code, and a passion for robustness and correctness.
• Software Engineering: Working on shared codebases to produce production quality code.
• Domain Knowledge – Computer Vision: Machine Learning techniques applied to image data.
• Deep Learning: Commercial experience working with Tensorflow or Pytorch and designing custom architectures and bespoke training methodologies.
• Scale: Working with large data sets, where data sets don’t fit into memory, and require multiple nodes to compute efficiently.
• Machine Learning: A strong grasp of machine learning fundamentals (regularisation, over-fitting, hyperparameter optimisation, validation methods).
• Leadership skills: Experience with leading technical teams and mentoring.

Highly Desirable:

• Domain Knowledge – Statistics: Data mining and statistical analysis techniques
• Cloud Computing: Experience with AWS or GCP.
• MLOps: Experience with operationalizing ML applications and workflows.
• Data: Experience with working with databases and preparing training and validation data.
• GIS: Knowledge of GIS tools and techniques.

Personal attributes:

• Pragmatism: While extensive knowledge of theory and best practices are highly valued, pragmatism wins over elaborate theory when it comes to shipping products that work
• Collaboration: data science is a team sport, communicate well, share knowledge, and be open to taking on ideas from anyone in the team.
• Attention to detail: Showing attention to detail when it counts is important... to be considered for this role, Click this link and apply some basic data science skills (an astute software engineer should be able to solve it quickly with a little googling!).

Tertiary Qualifications

Formal education in a technical, data related field

Some of our benefits

Nearmap takes a holistic approach to our employees’ emotional, physical and financial wellness. Some of our current benefits include competitive pay, access to the Nearmap employee share scheme, short and long-term financial incentives, flexible working options, paid volunteer days, gym and phone rebates, and lots of development opportunities including hack-a-thons and pitch-fests.

If you can see yourself working at Nearmap and feel you have the right level of experience, we invite you to get in touch.

Watch some presentations on what we do in the AI Systems group:

https://youtu.be/WSMYfAEdAe4

https://youtu.be/ZEGdSLWdrH0

https://youtu.be/JuHBJk2uuD8

https://youtu.be/8mSSG6uICW0

Nearmap does not accept unsolicited resumes from recruitment agencies and search firms. Please do not email or send unsolicited resumes to any Nearmap employee, location or address. Nearmap is not responsible for any fees related to unsolicited resumes.