Data Analyst (Statistics)

Maersk is a global leader in integrated logistics and have been industry pioneers for over a century. Through innovation and transformation, we are redefining the boundaries of possibility, continuously setting new standards for efficiency, sustainability, and excellence.



Join us as we harness cutting-edge technologies and unlock opportunities on a global scale. Together, lets sail towards a brighter, more sustainable future with Maersk.

We Offer

A tailored onboarding and induction with access to a wide range of training schemes to help with your learning and development. Setting you up for success is important to us.

An annual bonus based on company performance.

Every colleague at Maersk has access to a fantastic range of wellbeing, mental health support and financial advice through our Employee Assistance Program.

For eligible roles, we also offer short-term incentives to recognise, appreciate and reward your work for delivering outstanding results.

Whilst the role is advertised as full-time, we would be happy to discuss possible flexible working options and what that might look like for you.

Role: Data Analyst (JL2)

Work Experience: 2+ years experience.

Key Skills: Good experience as a Data Analyst or Machine Learning Engineer, with hands-on expertise in machine learning algorithms and models, statistical modelling, data visualization techniques, and core data science concepts. Proficiency in Power BI is required for data visualization, including creating interactive dashboards, report building, and data storytelling to drive actionable insights.

Should have strong proficiency in Python/R or any other analytical tool.
Hands on experience with libraries such as NumPy, Pandas, Seaborn, NLTK etc.
Should be experienced in SQL and operated on new age technologies like Azure, Teradata, Power BI etc.

Key Responsibilities:
Data Analysis & Visualization: Explore, analyse, visualize, and present data insights.
Trend Analysis: Identify and interpret trends and patterns in data.
Model Building: Use data tools to build models, create algorithms, and run simulations.
Stakeholder Collaboration: Work with various teams to understand needs and provide solutions.
Business Advisory: Advise stakeholders on data science applications for business outcomes.
Advanced Analytics: Expertise in developing data models, including prediction and forecasting models, data wrangling, data mining, and segmentation techniques, with a strong understanding of statistical models, machine learning algorithms, forecasting methodologies, and causality principles.
Team Guidance: Guide the team in identifying data trends and anomalies.
Data-Driven Culture: Promote data-driven decision-making and track model performance.
Communication: Present insights to stakeholders and in tech demos.
Team Collaboration: Collaborate with other data science teams to share learnings.
Proof of Concepts: Develop and assess new data science initiatives.

Business & Technical Skills:
Knowledge of methodologies to clarify business requirements, including design thinking, business process design, personas, user stories, etc.
Expertise in using analytical, statistical, and programming skills to collect, analyse, and interpret large data sets.
Ability to translate complex business problems into technical solutions, ensuring alignment with business objectives.
Experience in working with cross-functional teams to develop and implement data-driven strategies and solutions.

General Skills:
An excellent team player who balances strong autonomy with high motivation to produce individually.
Open to new ideas and innovative in approach.
Proactively learns new technologies and drives their adoption within their area of work.
Strong problem-solving abilities and a proactive attitude toward overcoming challenges.
Effective communicator with the ability to convey complex technical concepts to non-technical stakeholders.

Below are Plus:
Experience in developing real-world, impactful machine learning products
Familiarity with production-level best practices in Data Science and Machine Learning, including software engineering principles and product management
Knowledge of deep learning techniques for forecasting and recommendation systems
Understanding of Generative AI and Large Language Models (LLMs)

Qualifications:
Bachelor s or master s degree in mathematics, Statistics, Data Science, Machine Learning, or a closely related field.

Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. .

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