Senior Data Scientist / Data Engineer (R)

Senior Data Scientist / Data Engineer (R)Contract (6 months, full-time) | Melbourne / Hybrid | $1,000–$1,200 per dayAbout AptoNowAptoNow is a fast-growing software and analytics firm building the next generation of AI-powered solutions for higher education operations. Founded in 2021, we’ve quickly become a trusted partner to many of Australia’s leading universities, delivering measurable impact through intelligent data products and automation.Our team brings together deep expertise in data engineering, machine learning, and academic operations — with leadership from ex-McKinsey and Nous data scientists and consultants. We’re passionate about using data and AI to help universities operate smarter, plan better, and deliver exceptional student experiences.The RoleReporting to our Chief Data Scientist, this 6-month contract role is perfect for an experienced data scientist or data engineer who thrives on building robust data products and solving complex operational challenges in higher education.You’ll work across AptoNow’s data product portfolio — from our AI-Assisted Study Planning Tool to our Timetabling Balanced Scorecard — designing and deploying data pipelines, models, and production-grade R code that power decision-making at scale.Key ResponsibilitiesAs Senior Data Scientist / Data Engineer, you will:Design, build, and maintain ETL pipelines and data transformations across large, messy higher education datasets (student, curriculum, and timetabling data).Contribute to the development, testing, and deployment of AptoNow’s growing suite of R-based data products used by academic operations teams.Develop and optimise machine learning and rule-based models that improve operational efficiency and accuracy in planning and scheduling processes.Apply data modelling, statistical analysis, and optimisation techniques to drive actionable insights for universities.Implement robust data quality, validation, and reconciliation frameworks across multiple data sources.Participate in code reviews, CI/CD pipelines, and package development within our GitLab environment to ensure high standards of reproducibility and maintainability.Lead or mentor junior data scientists and contribute to our internal knowledge base on best practices in data science, R engineering, and AI deployment.Collaborate with cross-functional teams (e.g., product design, data visualisation, and client engagement) to translate analytical models into production-ready, user-centric tools.Support client implementations, including data mapping, onboarding, and automation rollout across university systems.Qualifications and ExperienceWe’d love to hear from you if you have:Expert proficiency in R, including RStudio, tidyverse, data.table, and related packages for data engineering and analytics.5+ years’ experience as a data scientist, data engineer, or similar role, with a proven track record of designing, developing, and deploying production-ready data products.Demonstrated experience working with complex relational data (e.g., academic structures, timetabling, curriculum, or operational data).Strong understanding of ETL/ELT pipelines, data quality frameworks, and workflow orchestration.Experience with optimisation, predictive modelling, or simulation techniques to support operational decision-making.Familiarity with AI, machine learning, or natural language processing (NLP) approaches in applied settings.Proficiency in GitLab, CI/CD workflows, and reproducible project structures (e.g., targets, renv, or similar).Exposure to Microsoft Power Platform, Power BI, or Shiny dashboards (nice to have but not essential).Excellent written and verbal communication skills — you can explain complex data concepts to non-technical audiences.A practical, problem-solving mindset — you enjoy translating messy, real-world data into elegant, usable solutions.What We OfferCompetitive daily rate ($1,000–$1,200 per day) on a six-month contract (with potential for extension).The opportunity to shape the future of academic operations using data and AI — and see your work implemented at scale.A collaborative, high-trust culture with experienced leadership and a transparent approach to growth.A flexible hybrid working model — split your time between our Carlton (Melbourne) office and remote work.Exposure to cutting-edge projects with leading Australian universities and growing international reach.