Sr. Data Scientist

Transact Campus is transforming the student experience through credential‑driven privileges, innovative commerce solutions and payments. Our enterprise‑class cloud platforms power campus life for millions of students and institutions.

Join as a founding member of our new Predictive Analytics team, where you'll work with Product teams to define our ML/AI development strategy and build our machine learning infrastructure from the ground up. This is a hands‑on, high‑autonomy role — you'll take full ownership of the model lifecycle, from data exploration through to deployment and monitoring in production, working directly on our Databricks on Azure architecture.

You’ll solve real‑world commerce and privileges problems — including order wait time prediction, market basket analysis, and conversational AI — while establishing the engineering standards and architectural decisions that will define how we build ML capabilities going forward. Your work will have direct, visible impact on our product and on the student experience for millions of users.

Location: Limerick City — Hybrid working 1 day per week / month on site (depending on location)

Employment Type: full time

Experience Level: Senior

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• Own the full ML lifecycle end‑to‑end — from data gathering, feature engineering, and model development through to deployment, serving, and production monitoring — without reliance on a dedicated MLOps function
  
• Design, build, and deploy ML models on Databricks, leveraging MLflow for experiment tracking and model registry
  
• Develop solutions for privileges and commerce‑focused use cases including order wait time prediction, market basket analysis, and demand forecasting
  
• Work with the Data Architect and Data Engineering team to design and build conversational AI and chatbot capabilities, leveraging LLMs and retrieval‑augmented generation (RAG) pipelines
  
• Collaborate with the Data Analytics team to leverage existing Power BI and Databricks data infrastructure, and extend it with predictive capabilities
  
• Define and implement MLOps best practices, CI/CD pipelines for models, and data governance standards — establishing the foundations the team will scale on
  
• Ensure data quality, security compliance, and model reliability in production
  
• Provide technical leadership and mentor AI/ML team members across Data Analytics and Predictive Analytics teams
  
• Partner with cross‑functional teams to find data‑driven opportunities and translate them into shipped ML features
  
• Stay updated on emerging technologies in AI, ML, and data science to drive innovation
  
• Provide technical leadership and help set the standard for ML engineering rigor as the team grows
  

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• 5+ years of experience taking ML models from development to production in a commercial environment, with a broader background in data science or engineering
  
• Deep, hands‑on experience with Azure ML and MLflow for experiment tracking, model registry, and model serving
  
• Strong proficiency in Python and SQL for data manipulation and analysis
  
• Proven experience deploying and monitoring ML models in production independently, without dedicated MLOps support
  
• Experience with ML frameworks - scikit‑learn, MLFlow, TensorFlow, PyTorch, and Pandas
  
• Experience with big data platforms (Databricks, Apache Spark) and cloud services (Azure Lakehouse, AWS, or GCP)
  
• Solid knowledge of ML Ops principles — CI/CD for ML, model versioning, drift monitoring, and pipeline automation
  
• Exposure to data visualisation tools (Power BI, Tableau, Looker)
  
• Strong knowledge of statistical modelling and the ability to select and justify appropriate approaches for real‑world problems
  
• Strong communication skills — ability to present complex technical concepts clearly to non‑technical stakeholders and influence product decisions with data
  

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• Master’s in Data Science, Computer Science or a related field
  
• Hands‑on experience with LLM frameworks such as LangChain, LlamaIndex, or similar, and familiarity with RAG pipeline design
  
• Experience with Databricks for ML workloads, including MLflow and Unity Catalog
  
• Experience in a commerce, fintech, or transactional data environment
  
• Familiarity with Apache Spark for large‑scale data processing
  
• Experience working in Agile/Scrum environments
  

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• Founding team member role — your architectural and technology decisions will shape how we build ML at Transact Campus
  
• Full ownership of the ML lifecycle with direct product impact
  
• Work with a modern data stack — Databricks, Azure, MLflow, Power BI
  
• Collaborative and supportive work environment with strong cross‑functional exposure
  
• Ongoing professional development and training opportunities
  
• Hybrid working model
  
• Regular social, sporting and community events
  

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• Private Health Insurance
  
• Dental Insurance
  
• Matched Pension Contribution
  
• 25 Days Annual Leave
  

This job description is not designed to contain a comprehensive listing of activities, duties, or responsibilities that are required. Nothing in this job description restricts management’s right to assign or reassign duties and responsibilities at any time. xcfaprz

Transact Campus Inc. is an equal employment opportunity employer and considers qualified applicants for employment without regard to race, gender, age, color, religion, national origin, marital status, disability, sexual orientation, protected military/veteran status, or any other protected factor.