About Dataro
Dataro is an ethically minded SaaS startup using machine learning to help not-for-profits raise more money and do more good. Our platform powers fundraising for organisations around the world, helping them run smarter campaigns and improve donor engagement using data-driven insights.
Machine learning isn't a buzzword at Dataro — it's the heart of our product. Every improvement you make to our models directly impacts real organisations and real causes in the world.
We're looking for talented engineers who have evolved into ML practitioners: people who enjoy writing high-quality software
and
working with data, models, and experimentation. If you want to build impactful ML systems inside a modern product team, we'd love to meet you.
The Role
As a Data Scientist Engineer, you'll work across our modelling pipeline, data platform, and product features to build and maintain the predictive models that power Dataro. You'll train, iterate on, deploy, and monitor models in production, while also contributing to the engineering systems that support them.
This role suits someone who started as a software or data engineer and now wants to go deeper into applied machine learning. You'll collaborate closely with product engineers, data scientists, and data engineers to deliver ML features at scale.
What You'll Do
* Train, debug, deploy, and monitor production ML models used by hundreds of organisations.
* Work with rich, complex datasets — including 100s of millions of records — to design new predictive features and improve model performance.
* Run controlled experiments to evaluate modelling approaches and pipeline improvements.
* Investigate and resolve issues in our modelling and data transformation pipelines.
* Contribute to the design and evolution of Dataro's ML infrastructure as our dataset and customer base grow.
* Work side-by-side with an experienced team of ML engineers, data scientists, and data engineers.
* Collaborate within a product team to bring ML-powered features into production.
What You'll Bring (Day One)
You don't need to be an ML specialist yet — but you
must
be a strong engineer with real-world ML exposure.
* Experience working on real machine learning projects (experimentation, training, deployment, monitoring).
* Strong Python skills, including writing production-ready, maintainable code.
* Strong SQL skills and comfort working with large, messy, real-world datasets.
* Understanding of databases, schemas, and general backend engineering practices.
* Ability to reason about data quality, statistical features, and modelling trade-offs.
* Bachelor's degree in Computer Science, Engineering, Mathematics — or equivalent practical experience.
Nice to Have (But Not Required)
No single person will have all of these — they're opportunities to grow.
* Experience in the fundraising or not-for-profit sector.
* Exposure to startups or fast-paced product environments.
* Experience with AWS services (EC2, Batch, Lambda, S3, Athena).
* Familiarity with analytical tools such as DuckDB or AWS Athena.
* Comfort with Git, CI/CD pipelines, and professional software workflows.
* Basic understanding of MLOps concepts (feature stores, model registries, experiment tracking).
Why You'll Love Working With Us
* Work on ML that produces
real-world
impact for charities and social causes.
* Apply your engineering skillset to meaningful problems at the intersection of data science and product development.
* Learn from and collaborate with a passionate, multidisciplinary team.
* Modern stack (Python, ML pipelines, Serverless AWS, Postgres, DuckDB, S3, Athena, etc.).
* We value smart engineers who understand how software works deeply — and aren't afraid to use modern AI tools to speed experimentation and improve ML workflows.
* Flexible working arrangements (WFH + office in Sydney).
* Friendly, transparent, mission-driven culture where your work truly matters.
Ready to code for impact?
Send your CV and answers to the three questions to
* Why do you want to work at Dataro?
* What is something you've built (outside of work) that you are really proud of?
* What is the hardest problem you've ever solved?
You must be based in Sydney and be able to demonstrate competence with Python, SQL and a solid grasp of ML fundamentals.