Data Scientist II
Geneva , Switzerland
vor 3 Tg.

Would you like to solve real world problems using advanced machine learning for the largest online travel company worldwide?

The Expedia Group team in Geneva helps our customers find and book the best travel for their needs, and our suppliers compete effectively and grow their business on our travel platform.

Our travel platform is powered through transforming raw data into insights that both suppliers and customers can leverage.

This role is for a Senior Data Scientist to join our growing Data Science team. We create state of the art machine learning models to make our travel platform more effective and efficient, increasing its relevance for travelers and travel partners (e.

g. hotels) worldwide. For example, we build models to forecast demand, to identify and address competitiveness gaps, and to give guided recommendations on how hotels can grow their business on our platform.

We strive to ensure everything we do has measurable business impact. We build innovative algorithms and models that make intelligent, automated decisions, both in batch and in real time.

We collaborate closely with the analytics, market management, product and technology teams.

In this position, you will drive key machine learning initiatives, using data on billions of platform interactions across more than a million hotels and other travel products worldwide.

You will utilize advanced machine learning and statistical modeling approaches to impact the business and raise the bar of how we work.

You will use the latest cloud and data technologies to train and deploy your models at scale and support key business initiatives.

Outstanding test-and-learn culture is essential to thrive in this fast-moving industry; if you can prove the positive impact of your approaches, you will quickly see them in production.

You are technically strong and possess excellent business acumen and communication skills. You can handle both planned and ad-hoc work, own important data products, prioritize workload effectively, and thrive in a dynamic environment.

You are self-motivated, a fast learner and work well under pressure to meet deadlines. Communicating your findings and implications to your teammates and to business partners clearly and concisely is key.

Who you are

MSc or PhD in a quantitative field like machine learning, computer science, statistics, applied mathematics / physics

3+ years industry experience; proven track record of applying innovative machine learning algorithms to business problems

Proven track record of working in projects involving cross-functional teams

Hands-on experience with a large array of machine learning algorithms and econometrics methods

Expertise in Python, R or Scala; good programing practice, ability to write readable, fast code

  • Good understanding of data technologies; Hadoop, Hive, Spark, and standard relational database structures along with query languages (SQL);
  • experience with the cloud services (AWS, Qubole, Databricks) a plus

    Familiarity with software engineering best practices, including version control, release management, incremental delivery, test-driven development, unit testing etc.

    Ability to understand a business problem, identify key challenges, formalize the problem from a data and algorithm perspective, and prototype solutions

    High intellectual curiosity and willingness to tackle complex / technical problems to generate actionable business insights

    Strong verbal and visual communication skills.

    What you will do

    Understand business challenges and formalize them into appropriate machine learning frameworks

    Gather and manipulate large volume of data, build datasets, select and engineer model features

    Develop, assess, and iteratively improve predictive models using advanced machine learning and statistical methods; Be able to debug and correct data assumptions through testing

    Collaborate with business partners, program management, and engineering teams to ensure that solutions meet business needs and have functional feasibility and robustness

    Communicate in a clear and concise manner to your peers and business stakeholders

    Develop a good understanding of the industry, our data landscape and how data science can help optimize the work of our business partners

    Keep abreast of latest data science development and share knowledge with the team

    Fulfill ad-hoc requests for data and analysis.

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