Transact Campus

Senior Data Scientist

Transact Campus

full-time

Posted on:

Location Type: Hybrid

Location: Limerick • Ireland

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Job Level

Senior

Tech Stack

ApacheAWSAzureCloudGoogle Cloud PlatformPandasPythonPyTorchScikit-LearnSparkSQLTableauTensorflow

About the role

  • 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, 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 rigour as the team grows

Requirements

  • 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
Benefits
  • Private Health Insurance
  • Dental Insurance
  • Matched Pension Contribution
  • 25 Days Annual Leave
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
machine learningdata gatheringfeature engineeringmodel developmentmodel deploymentmodel monitoringPythonSQLscikit-learnTensorFlow
Soft Skills
technical leadershipmentoringcommunicationcollaborationdata-driven decision making