Product Discovery Specialist

Role Summary

A techsavvy product incubation professional who blends strategic product thinking with handson discovery customer centric and rapid prototyping mindset. You will identify and validate highimpact opportunities build prototypes (from low to highfidelity) and turn evidence into derisked deliveryready bets - often leveraging modern AI/ML where it creates a clear customer and business advantage.

Core Responsibilities

Discovery & Incubation

Understand and represent the early stages of the Product Lifecycle with Design Thinking in mind.

Lead product discovery to identify customer problems validate opportunities and shape product direction before development begins.

Plan and run discovery activities: user interviews problemframing workshops assumption mapping journey mapping and rapid experiments.

Create prototypes from low to highfidelity (wireframes clickable flows service blueprints) to test desirability feasibility and viability.

Synthesize qualitative and quantitative insights into crisp recommendations hypotheses and nextstep experiments.

Collaborate closely with Product Design Engineering Data and Marketing to translate discovery outcomes into actionable delivery plans.

Define and track discovery success metrics to drive learning velocity and evidencebased decisionmaking.

Facilitate alignment across teams by communicating insights opportunity assessments and prototype learnings.

Champion a discovery culture - coaching teams on experimentation usercentricity and hypothesisdriven development.

AI/MLFluent Incubation (as relevant to a given concept)

Collaborate with executives PMs and stakeholders to prioritize AI initiatives where they create material customer impact.

Lead the design development and deployment of AI and UX tools models and systems to accelerate validation and pilot outcomes.

Make pragmatic architectural decisions that keep prototypes scalable efficient and robust as they move from lab to pilot.

Manage the full AI project lifecycle from research and prototyping to productionready handoff and monitoring plans.

Partner with backend/data engineering to productionize ML including pipelines feature stores evaluation and drift detection.

Mentor teammates and drive innovation by applying current AI research and best practices where they matter.

Required Skills & Experience

Product Discovery Expertise

Proven experience leading discovery in productled organizations.

Strong ability to identify user needs map journeys and uncover root problems.

Fluency with Opportunity Solution Trees JobstoBeDone Lean Startup and Design Thinking.

Prototyping & Experimentation

Scaleup/digital product team experience with fast iterative cycles.

Proficient with UX tools such as Figma/Sketch (or similar) and rapid prototyping techniques.

Experience designing/running A/B tests concierge/WizardofOz smoke tests and usability tests.

Ability to turn ambiguous ideas into tangible artifacts that drive decisions.

Research & Insight Generation

Skilled in user interviews usability testing and concept validation.

Able to analyze qualitative and quantitative data; familiarity with analytics tools (Amplitude/Mixpanel/GA) is a plus.

Collaboration & Communication

Strong facilitation for workshops ideation and alignment.

Clear concise storytelling to technical and nontechnical audiences; influence without authority across multiple teams.

Strategic & Analytical Thinking

Evaluate opportunities based on evidence business impact and feasibility.

Structured hypothesisdriven problemsolving; contributes to product strategy and roadmap shaping.

AI/ML Engineering Fluency (Handson Tshaped)

Strong foundation in Machine Learning & Deep Learning (neural networks optimization model evaluation).

Experience delivering enterprisegrade AI systems and leading crossfunctional AI initiatives.

Practical experience with LLMs/Transformers (e.g. BERT GPT LLaMA Mistral Claude Gemini) and prompt/evaluation frameworks.

Proficiency in Python SQL LangChain Hugging Face and MLOps practices.

Familiarity with Reinforcement Learning and multiagent systems for decisionmaking in dynamic environments.

Knowledge of multimodal AI (text image other modalities) and applied NLP/Text Analytics/Generative AI.

Cloudnative delivery on Azure (preferred) incl. Databricks Azure Web Apps and modern ML pipelines.

Competence in model evaluation & optimization monitoring and drift detection with appreciation for UX principles.

Domain Advantage (Big Plus)

Shipping logistics and/or supplychain management; transportation systems; marketplace/network platforms; exceptionmanagement and realtime operational decision systems.

What Youll Bring (Mindset)

Customer impact over hype; curiosity and handson bias;

balance rigor with pragmatism;

entrepreneurial ownership;

communicate prototypes through compelling narrative and UX journey;

move fast without sacrificing integrity;

thrive at startup velocity in realworld complexity

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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