Data Scientist

Keypath Education

2d•Remote

About The Position

Keypath Education is a leading EdTech company that partners with universities to design, launch, and manage high-quality online degree programs. We combine data-driven decision-making with deep sector expertise to help our university partners grow enrolment, improve student outcomes, and expand access to education. The Opportunity We are looking for a mid-level Data Scientist to join our Strategy & Insights team. Reporting directly to the Director of Data, Insights & AI, you will design and deliver predictive models and generative AI solutions that drive commercial outcomes across the student lifecycle. You will work across the full model development lifecycle—from problem framing and exploratory analysis through to deployment and monitoring—and collaborate closely with stakeholders across marketing, enrolment, student success, and product teams.

Requirements

Bachelor’s degree or Master’s degree in data science, statistics, computer science, mathematics, engineering, economics, or a related quantitative field.
3–5 years of professional experience in a data science, machine learning, or applied analytics role.
Experience directly managing or mentoring one or more analysts, including providing technical guidance, performance feedback, and professional development support.
Strong proficiency in Python for data science (pandas, scikit-learn, XGBoost/LightGBM, statsmodels, or equivalent).
Hands-on experience building and deploying predictive models in a commercial or operational context (not solely academic/Kaggle).
Practical experience with large language models (LLMs), including prompt engineering, fine-tuning, or building agentic AI workflows using frameworks such as LangChain, Semantic Kernel, or Azure AI Foundry.
Solid grounding in statistics and experimental design (hypothesis testing, regression, classification, time series).
Experience with MLOps practices: model versioning, CI/CD for ML pipelines, monitoring, and reproducibility.
Strong communication skills with the ability to present complex technical work to senior business stakeholders in a clear, outcome-focused manner.

Nice To Haves

Experience with Microsoft Azure cloud services (Azure ML, Azure AI Foundry, Azure OpenAI Service).
Familiarity with Microsoft Fabric, Databricks, or similar modern data platforms.
Experience with MLflow or equivalent experiment tracking and model registry tools.
Exposure to the education, EdTech, or student lifecycle domain.
Experience integrating model outputs into CRM platforms (e.g. Dynamics 365, Salesforce).
Familiarity with R for statistical modelling.

Responsibilities

Design, build, and validate predictive models (e.g. lead scoring, propensity modelling, forecasting, risk prediction) that inform operational and strategic decisions.
Develop and deploy generative AI solutions, including LLM-powered agents, retrieval-augmented generation (RAG) pipelines, and prompt engineering workflows to automate and enhance business processes.
Translate business problems into well-scoped analytical and modelling projects, working with stakeholders to define success criteria and measurable outcomes.
Perform feature engineering, model selection, hyperparameter tuning, and rigorous evaluation using appropriate statistical and ML techniques.
Productionise models into scalable, maintainable pipelines, collaborating with data engineering to integrate outputs into downstream systems (e.g. CRM, BI tools, operational dashboards).
Monitor model performance post-deployment, manage model drift, and implement retraining strategies.
Communicate findings and model outputs to non-technical stakeholders through clear visualisations, written summaries, and presentations.
Stay current with developments in applied ML and generative AI, and contribute to the team’s knowledge-sharing and capability-building efforts.
Provide guidance, direction, and oversight to one direct report within the Data, Insights & AI team.

Benefits

Flexible “Work Anywhere” model (remote, hybrid or office)
High-growth environment with strong career development opportunities
Collaborative, innovative, people-first culture
Certified as a Great Place to Work in Australia & Malaysia
A high-impact role in a growing Data, Insights & AI function with executive visibility.
The opportunity to work across both predictive ML and cutting-edge generative AI in a commercially grounded setting.
A collaborative, low-ego team culture that values learning, curiosity, and pragmatic delivery.
Professional development support, including access to certifications and training programmes.
Flexible working (remote, hybrid or office)
Employee Assistance Program and wellbeing initiatives
Access to LinkedIn Learning and career development programs
IT Equipment provided for your success