Principal Data Scientist (AI Output Systems team)Full-time

Company Description

Interested in building and executing geospatial analytics on top of millions of square kilometres of aerial imagery working closely with key property insurance customers? Nearmap is recruiting for a Principal Data Scientist to join the AI Output Systems team within the AI Systems group.

Nearmap is a Sydney-based global location intelligence company. 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 dating back to 2009. We produce automated 3D models of entire cities, and rich AI-driven vector maps, which turns our visual content into semantic information to power decisions in a wide range of organisations.

We are currently hiring a Principal Data Scientist to join our amazing, collaborative team. The AI Output Systems team we designs, builds, and operates software systems that transform aerial 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 computational geometry / GIS tools such as the Shapely and GeoPandas libraries.

Nearmap is a high-growth company, the ideal candidate will embrace an environment where things happen quickly and continuously. We aim for all employees to feel supported in their career development, with an abundance of opportunities for mentorship and cross-functional team projects.

Experience:
We are looking for highly skilled and experienced Data Scientist at Principal level with extensive industry experience and a track record of R&D achievements. Experience with designing and training custom production Machine Learning models is essential, as is the desire to build out a small team. We need our engineers to be collaborative, versatile, innovative team members with an enthusiasm for best practice, as we continue to push technology forward.

Job Description

A typical day will look like this:

• Work within a team to deliver end-to-end technical solutions - typically starting with spike sessions, onto architectural design and test creation, iteration on the solution, measuring quality and ultimately deploying to production.
• Participation in the design and scoping of greenfield projects, including customer exploration sessions.
• Commitment to best practices and a strong culture of peer review.
• Mentorship of team members and contributing as domain expert in a diverse team environment.

Qualifications

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 industry best practices such as a keen eye for clean code and a passion for robustness and correctness.
• Machine Learning: A strong grasp of machine learning fundamentals (regularisation, over-fitting, hyperparameter optimisation, validation methods).
• Leadership and collaboration skills: Experience leading and mentoring technical teams.

Highly desirable domain knowledge:

• Insurance: Understanding of the data needs of insurance risk modelling.
• Computer Vision: ML techniques applied to image data.
• Tabular Data: Generating predictive models from structured and unstructured data including time-series analysis.
• Working with large data sets, where data sets don’t fit into memory, and require multiple nodes to compute efficiently.
• GIS: Knowledge of geospatial tools and techniques at continental scale.

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/copy paste this link to solve a simple test [https://www.dropbox.com/s/flbmgxu0sc3e9xq/test_v2.psv?dl=0] and apply some basic data science skills. You can submit your answer in your application.

Tertiary Qualifications:
Formal education in a field related to numerical science (Bachelor’s degree in computer science, engineering, statistics, physics, etc.). Applicants with a Masters/PhD will fit in well within the team, but are by no means necessary - we’re more interested in what you can do!

Additional Information

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.

Read the product documentation for Nearmap AI:
https://docs.nearmap.com/display/ND/NEARMAP+AI

For a deep dive into Nearmap AI, listen to AI Systems Senior Director Mike Bewley on the Mapscaping podcast https://mapscaping.com/blogs/the-mapscaping-podcast/collecting-and-processing-aerial-imagery-at-scale

To hear an interview with Brett Tully, Director of AI Output Systems on the Super Data Science podcast, click this link: https://www.superdatascience.com/533

Watch our culture video and find out more about what a day in the life at Nearmap looks like.

Please note: Successful candidate must have full working rights to work in Australia. Unfortunately, we are unable to sponsor visas for overseas candidates at this stage.

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.