🚀 Internship

2023 Intern - Machine Learning Scientist - London (PhD)

Expedia Group

2mo ago

🚀 Off-cycle

London

🤑 £50k
Rolling basis

Description

Travel is so much more than simply reaching your destination. Along the way you will make an immediate impact on reimagining the way people search for travel with our awesome team by inventing brand-new techniques to power global travel for everyone, everywhere. From building pipelines and prototyping new ML models with A/B testing, to applying new techniques to services that run tens of thousands of requests per second, there is no shortage of opportunities for technical innovation at Expedia Group – the sky’s the limit!  

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Area of Responsibilities

Software Engineering

Responsibilities

Applying statistics methods like confidence intervals, point estimates and sample size estimates to make sound and confident inferences on data and A/B tests Applying Natural Language models to Google keyword analysis and applying meta models to our multi-objective ranking problem Communicating complex analytical topics in a clean & simple way to multiple partners and senior leadership (both internal & external)  Conducting feature engineering and modifying existing models/techniques to suit business needs Developing domain expertise in fraud & risk to understand how to detect risky transactions Modeling rich and complex online travel data to understand, predict and optimize business metrics to help improve the traveler experience  Framing business problems as data science problems with a concrete set of tasks  Apply your domain (i.e. travel, online retail) knowledge, business acumen (understanding the underlying business objectives), and critical reasoning skills to your work 
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Requirements

We know that many potential candidates can be hesitant to apply for a job if they aren't sure that they meet all the criteria shared. If you meet all the criteria labelled ‘Must’ and are interested in this role, we encourage you to apply!  Must be available to commit to the full program dates: June 26th, 2023 – September 1st, 2023 Must be graduating in 2024 with a PhD degree in a technical, or analytical-related, subject such as Computer Science (with focus in areas like Artificial Intelligence, Machine Learning, Natural Language Processing, Data Mining, Data Science), Mathematics, Physics, Statistics, Operations Research, Electrical & Computer Engineering, or any Engineering degree Must be willing to relocate to city of job location if outside commuting distance Must have Python and/or Scala, SQL knowledge  Must have no more than 2 years' professional experience  Helpful to have theoretical understanding various machine learning topics like Regression, Naïve Bayes, Deep Learning, Gradient Boosting, Random Forests, SVMs, Neural Networks Helpful to have experience with programming, statistical, and querying languages like Python, R, SQL/Hive, Java  Helpful to have understanding of distributed file systems, scalable datastores, distributed computing and related technologies (Spark, Hadoop, etc.); implementation experience of MapReduce techniques, in-memory data processing, etc.  Helpful to be familiar with cloud computing, AWS specifically, in a distributed computing context Helpful to be able to effectively communicate and engage with a variety of partners (e.g., internal, external, technical, non-technical people) Helpful to have Java, R, C++, Hive, Hadoop, Microsoft SQL Server knowledge 
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Benefits

Successful candidates will receive a competitive compensation package including the benefits below and others:   Travel discounts Relocation support (if eligible) 
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