Maersk

Associate Data Scientist

Bengaluru, India
Spark Python Azure Machine Learning
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Description

Are you enthusiastic about using data to optimize pricing in one of the world’s largest container shipping companies? Do you want to play a critical role in developing and implementing data-driven strategies for optimizing revenue for Maersk? Would you like to collaborate closely in a cross-functional team and tackle the challenge of communicating and working with a wide array of stakeholders?

As a Data Scientist in the Pricing Data Science team, you will design and build analytical models that enhance the accuracy of pricing recommendations in Maersk. You will be part of a strong team of data scientists, data engineers, and software engineers working together to build highly resilient, available, performant, and maintainable software.

How we work

We design data science products that unlock business value for our stakeholders across the global organization. We “Fail fast” and our teams are self-organizing and empowered, and we seek to constantly refine our processes to suit the current needs. We use modern analytical software tools, relying heavily on open source. Our stack is based on Databricks (I.e. Spark and Python) running in Microsoft Azure cloud.

Our culture is informal with teamwork, exploration, and rapid iteration at its core, and we believe that giving everyone a chance to be heard is the best way to achieve great results. We feel accountable for our work and take pride in creating high quality solutions. We value agility, respectful collaboration, knowledge sharing and the scientific method.

As a Data Scientist You Will

  • Perform data analysis and modelling to support pricing recommendation algorithms.
  • Develop, evaluate and deploy machine learning and optimization models that improve the accuracy of pricing recommendations.
  • Work with data and analytics experts to enhance and expand the functionality and possible use cases for our data-driven products that meet business requirements.
  • Work with relevant stakeholders to understand the business processes behind the data and the impact that data processing simplification can have on the final product.
  • Promote and drive adoption of cutting-edge data science practices within the team.
     

Who are we looking for?

  • You have a relevant university degree in a quantitative field, and perhaps some years of experience in data science or similar.
  • Preferably you have experience with platforms and technologies we use, but we value the right mindset, passion, and willingness to learn much more than knowing a specific technology or programming language.
  • You have an agile mindset, a learning mentality and care about great engineering culture and practices.
  • You are motivated by ensuring the models you develop accurately capture the underlying business processes and provide maximum value for the consumers, enabling more business value.
  • If you also happen to have experience with algorithmic pricing and associated domains (e.g. revenue management, demand modelling/forecasting) we will be extra interested in speaking with you!

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

Maersk
Maersk
Customer Service Information Technology Logistics Retail Shipping

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