Senior Applied Scientist, Machine Learning

Key Skills

Python Programming, AWS, Scala Programming

Job Description

We are the Data Team. A collective of specialists driven by our shared mission to help establish Xero as the most insightful and trusted small business platform. Our backgrounds and work are diverse—we work on data platforms, data modelling, application development, applied research, ethics, literacy, and strategy, to name a few. At the heart of our mission is helping our colleagues and customers get value from data responsibly, on robust data platforms, with robust methods.

Applied Scientists work in cross-functional teams (engineers, designers, product managers, etc) to create AI-powered experiences. We apply machine learning to develop products that reduce toil and provide insight, allowing small businesses to focus on what matters.

About the role

• There’s a myriad of job titles out there and the English language can only express so much in a couple of words. So role title aside, what we’re looking for is someone to:
• Be a leader in a cross-functional team and own key parts of delivering an ML product
• Make sure we’re solving the right customer problems, the right way (i.e. ethically)
• Educate colleagues and raise data literacy across Xero
• Keep up-to-date with the latest developments in ML, and figure out if and how we can use these advances to build amazing products
• Work with teams across Xero to improve data quality, and spot new opportunities to use data better
• Drive the adoption of best practices, and where necessary, create best practice
• Mentor and develop your colleagues, both in the team and across the company

About you

• You have 3+ years experience delivering web-scale production machine learning systems
• You rejoice in identifying tough problems that can be solved with the application of scientific thinking, algorithms and analytical data processing.
• You understand that solving worthwhile problems means covering all areas of the data lifecycle - finding it, understanding it, experimenting with it, despairing over it, fixing it, …
• You’re comfortable reading ML research papers, keep abreast of new work on arXiv.org and have on occasion spent your time tinkering around with that interesting new framework you read about recently ... but when it comes down to it, you want to solve real business problems in the simplest and most robust way possible.
• You’re comfortable working with experts from all corners of the company to deeply understand the customer problem before getting your hands dirty with all that data and code
• Experience as a hands-on practitioner building productionized machine learning pipelines which touch real human end users.
• You have a solid grasp of statistics and you have wrestled with the challenges inherent in actually measuring the impact of your machine learning pipelines in the wild
• You’ve learned through experience that it’s important to write testable, repeatable code so you can debug it when something goes bump in the night
• You know your way around the ‘nix command line, ssh your way happily around your multiple running AWS instances and are a competent programmer in Python, Scala or similar

What you'll bring with you

• Ability to translate between the business and machine learning domains
• Sound software engineering skills in Python, Scala, or similar
• Expert level hands on practitioner skills in one or more of: time series forecasting, natural language processing, classical machine learning, deep learning
• Ability to grasp and teach the mathematical concepts that underpin the domains outlined above
• Comfortable with version control and command line
• Strong communication skills and the ability to tailor a message for peers, senior stakeholders, and junior team members alike
• Ability to mentor and grow junior scientists