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Job Description

About Maersk: Maersk is a global leader in integrated logistics with a rich history of over a century, dedicated to setting new standards in efficiency, sustainability, and excellence. With a presence in 130 countries and a diverse workforce of over 100,000 employees, we shape the future of global trade and logistics through innovation and collaboration.

Job Level – Job Level 2

Work Experience: 5+ years’ functional experience

Required skill:

Minimum of 3 years of hands-on experience in Data Science, Machine Learning, and Deep Learning, with a specific focus on Natural Language Processing (NLP).

• At least 1 year of experience in developing Machine Learning products tailored for forecasting and optimization purposes.

• Proficient in practical Data Science and Machine Learning applications using Python, SQL and Spark.

• Thorough understanding of forecasting methodologies, algorithms, and causality principles.

• Demonstrated ability to grasp business requirements effectively and empathize with customer needs.

• Excellent communication skills with the capability to articulate complex analytical concepts to non-technical stakeholders.

• Hands-on experience in implementing Data Science and Machine Learning models as well as visualizing and communicating data and results effectively.

• Proactive self-starter and adept problem-solver capable of thriving in ambiguous environments.

you are responsible for:

  • Design appropriate solutions and data visualization strategies with recommended alternative approaches.

  • Build and deliver data engineering solutions in a team with E2E product responsibility

  • Develop, construct, test and maintain solution design to ensure on-going realization of business value from existing and new solutions

  • E2E product life cycle management including design, development, test, deployment, run, refactor and decommission.

  • Implement Scrum ways of working in projects.

  • Run sprint planning, backlog refinement, sprint retrospective, daily scrum, and other project planning meetings

  • Work on prioritized backlog based on business requirements by demonstrating Microsoft Azure Data capabilities e.g., Azure SQL, Integration, Data Bricks etc.

  • Develop solutions to provide BI visibility to support transformation and modernisation initiatives

  • Develop and maintain scripts for to execute automated BI reports, development tasks or support requests

  • Maintain technical documentation such as user guides, manuals and system specifications. Experience in building real-world, impactful ML products

  • Familiarity with best practices in production-level Data Science and Machine Learning, including software engineering principles and product management.

  • Knowledge of deep learning techniques applicable to forecasting and recommendation systems.

  • Generative AI & LLMs Knowledge

General Skills:

  • An excellent team player, balanced with strong autonomy and high motivation to produce individually

  • Maintaining effective relationships with a variety of stakeholders and business users

  • Someone who is open to new ideas and innovative in approach

  • Stakeholder management and interpersonal skills at both a technical and non-technical level.

  • Natural curiosity for learning and gaining business acumen

  • Proactively learns new technologies and pushes for driving the same in his space of work.

Qualifications:

  • Needs to be a graduate with post-graduation in Statistics/Data Science

  • Bachelor's or Master’s degree in Mathematics, Statistics, Data Science, Machine Learning, or a closely related field.

What We Offer:

  • Impact: Your work directly contributes to the success of our global operations.

  • Opportunity: Ample opportunities for professional and personal growth.

  • Innovation: Join a forward-thinking team embracing cutting-edge technologies.

  • Global Exposure: Collaborate with diverse colleagues in an international business environment.

  • Work-Life Balance: We value work-life balance and offer flexible working arrangements.

Join Maersk: Embark on a rewarding career journey with Maersk, where you'll contribute to redefining global logistics and trade while advancing your career in a dynamic and inclusive workplace.

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 accommodationrequests@maersk.com.

Company benefits

Open to part time work for some roles
Open to compressed hours
In house training
Health insurance
Dental coverage
Mental health platform access
Compassionate leave
Life assurance
Annual bonus
Referral bonus
Employee assistance programme
Employee discounts
Adoption leave
Private GP service
Buy or sell annual leave
Religious celebration leave
401K
Annual pay rises
Enhanced pension match/contribution
Learning platform
Mentoring
Enhanced maternity leave
Shared parental leave
Women’s health leave
L&D budget
Professional subscriptions
Lunch and learns

Working at Maersk

Company employees:

100,000+

Gender diversity (m:f):

65:35

Hiring in countries

Australia

Bangladesh

Brazil

Cambodia

Canada

Chile

China

Colombia

Czechia

Denmark

Egypt

France

Germany

Greece

Hong Kong

Hungary

India

Indonesia

Ireland

Italy

Japan

Malaysia

Mexico

Morocco

Netherlands

Pakistan

Panama

Peru

Philippines

Poland

Portugal

Romania

Saudi Arabia

Serbia

Singapore

South Africa

South Korea

Spain

Sri Lanka

Sweden

Taiwan

Thailand

Tunisia

Türkiye

United Kingdom

United States

Uruguay

Venezuela

Vietnam

Office Locations

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