Senior Data Scientist (Product)
Job details
Nearmap is unique. An Australian global technology company with incredible people; a market-leader with energy and spirit. Nearmap was named as one of the world’s 10 Most Innovative Companies of 2020 by Fast Company magazine – and we’re growing. Nearmap provides a virtual model of the real world – at a scale and detail that hasn’t been done before. Our ambition is to be the source of truth that shapes our liveable world. We are looking for an exceptional Senior Data Scientist with a keen eye for creating and critiquing high-quality, high-usability geospatial data. The Senior Data Scientist (Product) serves as a critical bridge between the AI Map Data team, vertical technical teams and the product team. We need a Data Scientist to be both a producer, and a consumer/critic, of the large-scale geospatial data we produce. Your job will be to become a part of the team producing and analysing this data, as well as collecting and interpreting customer feedback about that data. You will be pivotal in evolving the design and ontology of our systems, as well as developing key system-level metrics about our data that help us improve, and help our customers use and trust our data. You will be comfortable operating in a team of largely ML Engineers to integrate these metrics into regular evaluations, identify system optimisations, and design streamlined processes for system releases. This role involves creating comprehensive documentation and serving as a key technical resource for customer and internal communications on Map Data products. A typical day will look like this
- Work within a team to deliver end-to-end technical solutions — typically starting with spike sessions, onto method and dataset design and test creation, iteration on the solution, measuring quality, and communicating results both internally and to customers.
- You will work with datasets larger than memory and must be comfortable wrangling code in order to make this manageable.
- Commitment to software best practices and a strong culture of peer review.
- Demonstrated history working in a numerical field: e.g. computer vision, applied maths, physical sciences, geospatial analysis.
- Strong approach to systems thinking, whilst remaining pragmatic.
- A scientific mindset of formulating hypotheses, and applying statistical tests to validate them.
- Commitment to software engineering principles for scientific python, a keen eye for clean code, and a passion for robustness and correctness.
- Working on shared codebases to produce production quality code.
- Working on Machine Learning problems applied to earth observation data.
- Working with large data sets, where data doesn’t fit into memory, and requires multiple nodes to compute efficiently.
- Working in a cloud-native environment using highly scalable compute.
- Data science is a team sport; communicate well, share knowledge, and be open to taking on ideas from anyone in the team.
- While extensive knowledge of theory and best practices are highly valued, pragmatism wins over elaborate theory when it comes to shipping products that work.
- Quarterly wellbeing day off - Four additional days off a year as your "YOU" days
- Access to LinkedIn Learning
- Team Hackathons and Pitch-fests
- Wellbeing and technology allowance
- Nearmap subscription (of course!)
- Stocked kitchen with access to all the sustenance you need
- In-office Lunch every Tuesday and Thursday at our Sydney CBD office
- Showers available for anyone cycling to work or lunchtime gym-goers!
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