Xero is a beautiful, easy-to-use platform that helps small businesses and their accounting and bookkeeping advisors grow and thrive.
At Xero, our purpose is to make life better for people in small business, their advisors, and communities around the world. This purpose sits at the centre of everything we do. We support our people to do the best work of their lives so that they can help small businesses succeed through better tools, information and connections. Because when they succeed they make a difference, and when millions of small businesses are making a difference, the world is a more beautiful place.
About the Team
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 ML-inside 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 and views on what machine learning scientists do. At Xero, we're looking for someone to:
- Provide leadership to cross-functional teams that build web-scale ML-inside products
- Work with your peers and the Data Leadership Team to define the roadmap for Applied Sciences
- Identify cross-cutting opportunities to create frameworks / tooling
- Work with other scientists to figure out the best practices for reproducible and robust science
- Keep up-to-date with the latest developments in ML, identifying opportunities for Xero to improve #beautiful products
- Be comfortable with pushing the frontiers of ML in the pursuit of delivering products, but only where absolutely necessary
- Make sure our work is always in the best interests of our customers
- Align multiple programs of work so that they benefit each other
- Identify new ML product opportunities and work with product teams to determine if they’re worth pursuing
- Create the culture that means people love working with us
- Mentor, manage, and develop other scientists and colleagues
About You
You have extensive experience delivering production machine learning systems
You rejoice in identifying tough problems that can be solved with scientific thinking
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 productionised 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
You’ve mentored and grown teams of applied scientists, teaching the skills of scientific reasoning, collaboration, and effective program delivery
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
Please mention that you found the job at Jobhunt.ai
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