Full Stack Data Scientist

Build data products. Solve real business problems. Shape the future of shipping. Join Höegh Autoliners as a Full Stack Data Scientist and work across the full data and analytics lifecycle—from understanding business problems and wrangling data to building predictive models, AI-enabled applications and decision-support tools. You’ll work closely with stakeholders across the organisation and collaborate with data engineers, software developers and business teams to turn data, machine learning and emerging AI technologies into solutions that create measurable business value. If you enjoy combining strong analytical thinking, programming and business understanding—and want to see your work move from idea to production—this is an opportunity to make an impact. A Full Stack Data Scientist in Höegh Autoliners will be given the opportunity to: Build end-to-end predictive, descriptive and AI-enabled analytics solutions. Understand business problems and use data visualisation, analytics tools, statistics, machine learning and artificial intelligence to deliver business insights and solutions. Present, analyse, visualise, wrangle, model and structure data. Develop data products, analytics solutions and AI-enabled applications using modern cloud technologies. Work with decision makers across all organisational levels, functions and cultures. Main Responsibilities Participate in all activities across the data and analytics lifecycle. Source, collect, integrate, structure and wrangle relevant information from multiple sources, extracting insight for better business understanding. Communicate and present findings to stakeholders using a variety of formats and visualisation tools. Design actionable data products based on statistical analysis, machine learning and AI methods, and support their adoption across the business. Identify opportunities where machine learning and Generative AI can improve business processes, productivity and decision-making. Develop and evaluate analytics, machine learning and AI-powered solutions using Microsoft Azure and related technologies. Work collaboratively with data engineers, software developers and business analysts in an agile environment. Education and Experience Strong programming skills in Python, R and/or SQL. Experience with Power BI, Qlik, Tableau or similar business intelligence and visualisation platforms. Knowledge of statistical methods, machine learning algorithms and modern AI techniques. Exposure to Generative AI technologies, large language models and prompt engineering. Experience with Microsoft Azure, cloud-based data platforms or related cloud technologies. Experience with data engineering concepts and ETL/ELT technologies. Familiarity with Azure AI Foundry, Azure OpenAI Service or similar AI development platforms is an advantage. A drive to learn and apply modern technologies and techniques. A Master's degree in a computational, mathematical or statistical discipline is preferred but not required. Proven experience and successful delivery of business value will be weighted as heavily as formal qualifications. We believe that building and sustaining a diverse and inclusive environment for working and learning leads to a better workplace, better ideas and more inspiring conversations.