AIML Scientist (Applied Scientist)
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Job Summary
A.P. Moller - Maersk
A.P. Moller Maersk is the global leader in container shipping services. The business operates in 130 countries and employs 80000 staff. An integrated container logistics company Maersk aims to connect and simplify its customers supply chains.
Today we have more than 180 nationalities represented in our workforce across 131 Countries and this mean we have elevated level of responsibility to continue to build inclusive workforce that is truly representative of our customers and their customers and our vendor partners too.
The team - who are we:
You will join a technical team of around 50 people in APM Terminals building the systems behind some of the worlds leading container terminals where the cranes move the yard fills up and the vessel is waiting.
What makes this work inspiring is how close it sits to the operation.Your models are not evaluated in isolation: they are discussed with the people who run the terminal and measured against what actually happens there.Getting that right is demanding and it is what makes the results worth something.
Our backgrounds span operations research simulation machine learning software engineering and terminaloperations themselves. Nobody here covers all of it and that is deliberate the most interesting problems tend to sit between two peoplesexpertise.
Your Impact
You will be part of the APM Terminals technical team. As an Applied Scientist you will have a key role in designing buildingmaintaining anditerating ondata-driven products that directlyimpactterminal operations. This position offers a unique opportunity to apply your technical knowledge to create operational and strategic insights that are transforming container terminal operations globally. This is an exciting time to join a growing and dynamic team that solves some of the toughest problems in terminal operations and builds the future of container shipping. We offer a unique opportunity toimpactglobal trade via world-leading container terminals.
Key Responsibilities
Design implement and deliver advanced solutions for terminal operations including container handling equipment efficiency yard positioning strategies vessel loading/unloading sequencing and vehicle routing contributing to system design architecture and solution design as new features take shape.
Build both operational tools for real-time day-to-day terminal operations and strategic models for long-term planning and decision-making.
Act as the bridge between the physical yard and the code translating messy stochastic physical realities into logical mathematical models.
Explain complex model rationale and results to non-technical terminal operators and leadership to build trust and successfully roll out solutions to production environments.
Monitor model performance against actual physical terminal events iteratively improving models to handle operationaldriftand increase effectiveness.
What You Bring (The T-Shaped Profile)
We are looking for hybridproblem-solvers.We do not expect you to know everything; rather we want to see a solid technical foundation combined with real depth somewhere.
The Core Foundation (Required)
Experience:We typically look for 5 years of industry experience building and delivering technical or optimization solutions. This is a guideline not a filter a strong PhD or exceptional demonstrated ability can substitute for part of it. We do expect some industry experience: you should have shipped something real that people depend on.
Education:. or PhD in Operations Research Industrial Engineering Machine Learning Statistics Applied Mathematics Computer Science or a related quantitative field or equivalent practical depth.
Production Python:Track record of delivering production-quality Python code for data-centric applications specifically integrating models (e.g.machine learning optimization simulation or statistical logic) into functional software.
Systems-level problem solving:You canobservea physical operational bottleneck frame it mathematically and objectively decide the best analytical tool to solve it.
Your Area of Expertise
We are looking for depth breadth or a mix of the two. Either works:
Advanced depth in one of the areas below or
Solid working knowledge across two or more of them.
Operations Research (OR):Depth in optimizationmodelling LP MILP constraint programming and/or metaheuristics applied to problems like scheduling sequencing routing bin packing and resource allocation. Fluency implementing these in Python across open-source and commercial solvers (e.g.PuLP OR-Tools/CP-SATHiGHSGurobi).
Discrete Event Simulation (DES):Experience developing models for stochastic operationalenvironments andevaluating solutions against simulation.
Statistical Modelling:Fitting andvalidatingstatistical models of operationalbehaviour dwell time distributions arrival processes equipment cycle times and applying them to capacity analysis as inputs to simulation models or for inference.
Machine Learning / AI:Experience using AI/ML methods for operational problems or prescriptive analytics (e.g.stochastic optimization reinforcement learning).
Nice to Have
Not required but it will accelerate your ramp-up:
Container terminal operations portlogistics or comparable operational environments with complex resource allocation and scheduling dynamics container handling equipment yard operations or vessel operations.
Material handling manufacturing operations or other domains involving physical asset optimization and sequencing problems.
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.
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CORE SKILLSData Analysis: The process of inspecting cleansing transforming and modeling data to discover useful information draw conclusions and support decision-makingProficiency Level: ProficientStatistical Analysis: The process of collecting and analyzing data to identify patterns and trends and to make informed Level: ProficientAI & Machine Learning: The field of artificial intelligence (AI) involves creating systems that can perform tasks that typically require human intelligence. Machine learning (ML) is a subset of AI that uses algorithms to learn from and make predictions based on dataProficiency Level: ProficientProgramming: Writing code to manipulate analyze and visualize data often using languages like Python R and Level: ProficientData Science: A multidisciplinary field that uses scientific methods processes algorithms and systems to extract knowledge and insights from structured and unstructured Level: ProficientSPECIALIZED SKILLSData Validation and Testing: Ensuring that data is accurate and meets the required standards before it is used in analysis or Deployment: The process of making a trained machine learning model available for use in production Learning Pipelines: Automated workflows that manage the end-to-end process of training and deploying machine learning Learning: A subset of machine learning involving neural networks with many layers used to model complex patterns in Language Processing (NLP): A field of AI that focuses on the interaction between computers and humans through natural & Scientific Computing: Using Mathematical techniques and computational algorithms to solve complex problems and optimize processesDecision Modeling and Risk Analysis: Decision Modeling and Risk Analysis are methodologies used to make informed data-driven decisions under uncertainty especially when multiple factors and possible outcomes need to be Documentation: Creating and maintaining documentation that explains the functionality use and maintenance of software or of Proficiency Levels:Foundational: This is the entry level of the skill typically expected when starting a new role or working with the skill for the first time. You rely on strong manager support coaching and training as you build the capability to progress to higher proficiency : This is the level at which you are considered effective in the skill. You demonstrate more than just functional competenceyou begin to have a noticeable impact in your role by applying the skill consistently and meaningfully. You require only minimal support coaching or training to apply the skill : This is the level where you move beyond meeting expectations to actively leading influencing and delivering considerable impact across the wider business. You are seen as a role model demonstrate the skill independently and require little to no manager support.Required Experience:
IC
About Company
Maersk Line is a Danish international container shipping company and the largest operating subsidiary of the Maersk Group, a Danish business conglomerate. It is the world's largest container shipping company by both fleet size and cargo capacity, serving 374 offices in 116 countries
