- Use soft skills and technical skills in ML building recommender systems!
- ASX top 100 company with 5.5 million loyalty members and growing!
- Awesome team. Autonomy. New projects. Great tech.
This is a truly exciting opportunity for an experienced data scientist to join a fast-growing data science team that is building state-of-the-art machine learning recommendation solutions. This company has a very large investment in data and some talented data science and ML engineering peers. They are at a very exciting stage of growth right now and have over 5.5m loyalty customers and have several initial recommendation engines running in production.WHY IS THIS ROLE DIFFERENT???
ABOUT THE JOB:
- Join at an early stage - most ML projects are still greenfield and will be in the space of productionised, scalable Personalisation and Recommendation engines built in Databricks/Spark and Python
- You will work with a highly technical data science leader who cares deeply about building one of the top data science and ML teams in Australia. She is also friendly, supportive and effective managing stakeholder expectations.
- You have lots of responsibility, autonomy and flexibility to contribute to key decisions with both strategy and technical delivery of ML solutions
- This team is a not an academic team (no offence!) They are kicking-goals and deploying models that can quickly have a large impact on product, marketing, customer experience and bottom-line profit!
You will be part of a 10-person data science team, but often you will in cross-functional Product teams. You will lead data science strategy, discussions and design experiments and solutions - with a core focus on automating personalisation of marketing using ML.
Because you will be exploring new applications of ML for the business and to deliver a better Customer Experience, we need you to be an experienced communicator with non-data specialists.ABOUT YOU:
You will need to have at least 3 or more years of professional data science experience in a business domain that is relevant (could be analytics consulting, retail, telco, banking, e-commerce, but preferably a business with millions of customers).
This role will suit you if you have a preference for working end-to-end, starting from business problems and questions - all the way through to data exploration, experiment design, modelling and serving models/insights.
We also like people who have had experience building and deploying models in production in a modern big data stack so you'll need professional experience in Spark, Python and SQL with one of the cloud platforms.
The main team is in Sydney but we are flexible to some team hires being based full-time in Melbourne (satellite office).
Academic background at a bachelor, masters or PhD level - we are open to diverse backgrounds but it should include a numerical foundation, such as Mathematics, Statistics, Physics, Computer Science, Mechanical Engineering, Actuarial Studies, etc.More detailed information will be discussed with shortlisted candidates. Interviews have already begun - please apply soon if you are interested!