Senior Data Scientist, Multiverse

• 5+ years of data science/machine learning experience, with a proven track record building and deploying models that drive real business decisions
• Deep expertise in predictive modelling, forecasting and/or optimisation - with strong command of the underlying statistical principles
• Strong proficiency in Python and core ML libraries (e.g., NumPy, Pandas, Scikit-Learn, xgboost, shap)
• Advanced working knowledge of SQL
• Hands-on experience with data pipelines and ML infrastructure
• Experience working within AWS (ideally using Sagemaker) and/or Azure
• Comfort working across our data stack - inc Airflow, Snowflake
• Experience with version control and CI/CD practices (ideally using GitHub)
• Rigorous attention to statistical validity - comfortable challenging assumptions and defending methodology
• Understanding of best practices in data protection and information security

Desirable

• At Multiverse, the models we build don't just sit in notebooks - they drive the decisions that shape our business every day
• From predicting learner outcomes to forecasting operational demand and optimising how we allocate resources, this work sits at the very core of how we run the company
• As a Senior Data Scientist, you'll own these models end to end. You'll develop a deep understanding of how Multiverse operates across our customer, learner and operational domains - and translate that understanding into rigorous, production-grade ML models that genuinely move the needle
• To be successful, you'll be comfortable getting hands-on with pipelines and infrastructure - and unafraid of the statistical rigour that serious modelling demands
• You'll work closely with stakeholders across every part of the business - helping them ask better questions, understand the answers, and act on them with confidence
• Our leaders will make multi-million dollar decisions based on your recommendations, and our AI-powered product will decide how to support learners based on your models
• You'll sit within our Data & Insight team, working day-to-day alongside Data Engineers, Data Product Developers and Insight Analysts
• Building genuine expertise in how Multiverse operates across customer, learner and operational domains - becoming a trusted thought partner
• Translating complex and often ambiguous business questions into well-scoped modelling problems with clear success criteria
• Identifying where predictive, forecasting or optimisation models can have the greatest business impact, and prioritising accordingly
• Designing, developing and iterating supervised and unsupervised ML models that predict, forecast and optimise across the business
• Applying rigorous statistical methods to ensure models are robust, unbiased and genuinely causal wherever causal claims are being made
• Developing a deep understanding of our data landscape - its lineage, quirks, and limitations - and designing approaches that account for them
• Monitoring and refining models over time, ensuring they remain accurate and relevant as the business evolves
• Collaborating closely with Data Engineers to build and maintain the data pipelines and ML infrastructure needed to develop and deploy your models
• Productionising models to run reliably at scale, adhering to software engineering best practices - including version control, CI/CD and vulnerability management
• Evaluating and implementing scalable approaches to data collection and processing, ensuring robust practices are in place