Job
Description
Our new member - who are you You are driven by curiosity and are passionate about partnering with a diverse range of business and tech colleagues to deeply understand their customers, uncover new opportunities, advise and support them in design, execution and analysis of experiments, or to develop ML solutions for ML-driven personalisation (e.g., supervised or unsupervised) that drive substantial customer and business impact. You will use your expertise in experiment design, data science, causal inference and machine learning to stimulate data-driven innovation. This is an incredibly exciting role with high impact. You are, like us, a team player who cares about your team members, about growing professionally and personally, about helping your teammates grow, and about having fun together. Basic Qualifications: Bachelors or masters degree in computer science, Software Engineering, Data Science, or related field 35 years of professional experience in designing, building, and maintaining scalable data pipelines, both in on-premises and cloud (Azure preferred) environments. Strong expertise inworking with large datasets from Salesforce, port operations, cargo tracking, and enterprise systems etc. Proficient writing scalable and high-quality SQL queries, Python coding and object-oriented programming, with a solid grasp of data structures and algorithms. Experience in software engineering best practices, including version control (Git), CI/CD pipelines, code reviews, and writing unit/integration tests. Familiarity with containerization and orchestration tools (Docker, Kubernetes) for data workflows and microservices. Hands-on experience with distributed data systems (e.g., Spark, Kafka, Delta Lake, Hadoop). Experience in data modelling, and workflow orchestration tools like Airflow Ability to support ML engineers and data scientists by building production-grade data pipelines Demonstrated experience collaborating with product managers, domain experts, and stakeholders to translate business needs into robust data infrastructure. Strong analytical and problem-solving skills, with the ability to work in a fast-paced, global, and cross-functional environment. Preferred Qualifications: Experience deploying data solutions in enterprise-grade environments, especially in the shipping, logistics, or supply chain domain. Familiarity with Databricks, Azure Data Factory, Azure Synapse, or similar cloud-native data tools. Knowledge of MLOps practices, including model versioning, monitoring, and data drift detection. Experience building or maintaining RESTful APIs for internal ML/data services using FastAPI, Flask, or similar frameworks. Working knowledge of ML concepts, such as supervised learning, model evaluation, and retraining workflows. Understanding of data governance, security, and compliance practices. Passion for clean code, automation, and continuously improving data engineering systems to support machine learning and analytics at scale. Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements. We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing .
