Job Title

About the company for Stolt Nielsen:Stolt-Nielsen is a family-founded global leader in bulk-liquid and chemical logistics, transportation, and storage, known for its commitment to safety, service excellence, and innovation. At the Stolt-Nielsen Digital Innovation Centre, we bring this legacy into the future — building smarter systems, driving digital transformation, and shaping what's next for the world of logistics. Here, you’re encouraged to think boldly, challenge convention, and help move today’s products toward tomorrow’s possibilities.About the Role:We are seeking a Senior Data Scientist with a passion for solving complex problems using data, AI, and automation. In this role, you will design, develop, and deploy predictive and analytical models using Python, pandas, scikit-learn, OpenCV, and AutoML frameworks — all within a Databricks environment powered by the Mosaic ML stack.You’ll work at the intersection of analytics, AI, and engineering to turn data into insights and intelligence that drive business outcomes.At Stolt-Nielsen, we take Digital seriously. We invest in our teams through training and mentoring and enable them with the required tools to work in a modern way. As we are further building up our engineering practice, there is ample room for you to contribute, take initiative and shape the future of our ways of working and technology landscape.What You’ll Do:- Explore, clean, and analyze data using Python, pandas, and SQL to uncover patterns, trends, and opportunities. - Develop and train machine learning models (supervised and unsupervised) using scikit-learn, AutoML tools, and Mosaic ML workflows. - Apply computer vision techniques with OpenCV and deep learning libraries for image-based use cases. - Operationalize models in Databricks, collaborating closely with data engineers and analysts to ensure scalability and performance. - Build end-to-end ML pipelines, from data ingestion and feature engineering to model deployment and monitoring. - Experiment with Mosaic ML and Databricks MLflow for reproducibility, optimization, and lifecycle management. - Communicate results and insights through clear visualizations, reports, and presentations to technical and non-technical audiences. - Stay current on new methods in ML, AI automation, and data science tooling.What You’ll Bring:- Bachelor’s or master’s degree in computer science, Machine Learning, Artificial Intelligence, or a related field. - 5+ years of hands-on experience in data science, machine learning, or AI engineering roles. - Strong proficiency in Python and data science libraries (pandas, NumPy, scikit-learn, matplotlib, seaborn). - Practical experience building, evaluating, and deploying models in Databricks (MLflow, Delta, notebooks). - Experience with AutoML frameworks (e.g., H2O.ai, AutoGluon, or Databricks AutoML). - Familiarity with Mosaic ML or other MLOps optimization frameworks. - Knowledge of YOLO/OpenCV for computer vision; use of Generative AI and LLMs. - Strong foundation in statistics, machine learning, and data visualization. - Ability to translate business problems into analytical solutions with measurable impact.Must Have Skills:- Python - SQL - MLFlow (Databricks good to have) - Preferred Azure services (storage, compute)/AWS/GCP - GIT and basic understanding of CI/CD and Infrastructure-as-Code (we use Azure DevOps) - Additional – Problem solving skills