ABOUT THE TEAM

The Product Data Science & Engineering team reports into Xero’s Product function. We are responsible for empowering Xero to deliver successful customer outcomes through actionable insights and analytics.
Our team supports product teams with key information to: understand the current product landscape and user behaviour, inform and motivate product behaviour and shape product strategy.
As our function evolves, we are increasingly supporting the deployment and operationalization of machine learning models to deliver intelligent, data-driven products and services.
We do this by creating, managing, and delivering a wide range of analytical services including core reporting, key data dimensions, extensible analytical assets, and robust data pipelines for machine learning applications.
We aspire to advance a culture of data-driven decision making, made possible through high quality, timely assets, insights, and increasingly, through the delivery of ML/AI powered predictions and optimisations.

ABOUT YOU

We’re looking for someone who can hit the ground running, working with our counterparts in divisional pods and the applied data science teams. You’ll deliver outputs for stakeholders across Product, with an increasing focus on enabling AI/ML powered insights.
We’re seeking an individual with prior experience in delivering data or analytics engineering outputs, who is keen to work through challenging problems, and possesses a strong aptitude for Python and software engineering principles. You will help us grow our capabilities in supporting the machine learning lifecycle.
Our team is responsible for ensuring our analytics and data infrastructure aligns with best practices in engineering and operations. You will contribute to and learn from a culture focused on technical excellence, reusability, continuous improvement, and the operationalisation of data science.

OUR PURPOSE

At Xero, we’re here to help you supercharge your business. We do this by automating routine tasks, surfacing actionable insights and connecting businesses with the right data, advisors and apps. When that happens, we’re not only making life better for small business, we’ll be building a stronger economy that can change the world.

ABOUT THE ROLE

As an Analytics Engineer supporting Product Data Science, you will be responsible for delivering high-quality data assets (data pipelines and models) that enable both rapid decision-making and the development and deployment of machine learning models.
This role will play a crucial role in bridging the gap between traditional analytics engineering and the growing needs of our machine learning initiatives.

WHAT YOU’LL DO:

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• Undertake technical discovery with stakeholders, and understand the business context in designing and implementing solutions for data pipelines, models and applications.

• Develop robust and scalable data pipelines and models using Python, SQL, and our evolving data stack (e.g., DBT, Snowflake, and MLOps tooling).
• Model data for optimal workload consumption, eg analytical, BI, ML modelling.
• Develop and maintain infrastructure, tooling, and monitoring for data applications and reproducible data science workflows.
• Contribute to our library of analytical assets, including our feature store, enabling self-service analytics and reducing time spent on data wrangling.