Graduate Machine Learning Scientist II - 2024 - London

Key Skills

AWS, Azure, Linux Operating system, R Programming, SQL, UI design, UX design

Job Description

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Role Summary

An established performer who consistently applies the data science capabilities, principles and playbooks to solve business issues and opportunities.

Experience

• 0-2+ years for Bachelor's
• Typical entry for Master's
• Use high end of range for PhD

Education

• Built and maintained multiple data science project/product in production environments.
• Participated and submitted to 5 or more data science competitions (such as Kaggle).

Bachelor's, Master's, PhD or equivalent experience. Technical or scientific degree preferred.

• Functional/ Technical Skills
• Supervised Machine Learning
• Unsupervised Machine Learning
• Reinforcement Learning
• Machine Learning Software Development Life Cycle
• Computing Language Skills (Python or Java, SQL)
• Training Data Management & Feature Engineering
• Visualization
• Business Acumen
• Active Listening
• Communication and Influencing
• Critical Thinking
• Problem Solving
• Project and Stakeholder
• AI Ethics

Role Expectations

• Is familiar with Python, Scala or R, or any other major ML programming language.
• Extracts data from multiple data sources and combine into the required datasets for model building or analytics.
• Applies software design principles, data structures, algorithms and computer science fundamentals to write code that is clean, maintainable, optimized, modular with good naming conventions for analytics or machine learning.
• Performs proper model performance evaluation with help.

• Has a basic understanding of supervised machine learning theory and techniques.
• Has 1-2 years or no experience in machine learning.
• Develops basic solutions utilizing standard software libraries/packages.
• Provides significant help in all activities, especially in proper model selection, regularization and evaluation to be able to develop robust solutions.
• Spends a large amount of time in feature engineering, is less capable to adapt/modify existing models/techniques to suit business needs.

• Applies a range of common statistical methods to business problems.
• Determines the ideal method for the problem considering underlying assumptions.
• Understands limitations of selected methods.
• Understands both frequentist and Bayesian statistics.
• Has a solid understanding of hypothesis testing.
• Designs complex experiments.
• Applies common methods such as linear and non-linear regression, multivariate analysis, etc.
• Understands model design and can explain selection, including general approach, choice of algorithm and data sources.
• Engages with research community and can make recommendations and apply concepts to current projects.
• Demonstrates understanding of business domain and can recommend model changes constantly evolving information and requirements.
• Selects valid approaches, appropriate in terms of level of effort, favoring iterative delivery that solve for the objective, not the ask (i.e. not just order-taking).
• Demonstrates an understanding of functional technical information (e.g. user flows, technical system design and workflows).
• Knows and applies data visualization principles consistently to result in clear and consistent outcomes.
• Builds complex charts with limited supervision.
• Consistently uses color palettes effectively and is aware of end user fatigue.
• Creates clear and consistent visualizations with feedback from peers and stakeholders.
• Familiar with basic UX and UI concepts.
• Embeds visualization from tools utilizing basic techniques such as iframes.
• Is familiar with EG visualization tool ecosystem and uses most features to create charts.
• Clearly and confidently articulates decision-making rationale, solutions, methodologies and frameworks to team members and both technical and non-technical partners.
• Anticipates and assists team members with the creation of routine technical communication materials (e.g., policies & procedures, guidelines, presentations, messages).

• Proactively contributes to cross-team collaboration to ensure the best available information is included, and shares findings with peers and leaders.
• Considers the audience's needs and context when crafting solutions or presenting ideas and identifies how the needs may differ by audience.
• Influences action and results through writing clearly, in an accessible way for a wide audience. Anticipates questions and structures presentations around a clear narrative, and is concise in what's included. Presents in a clear and engaging manner.
• Frames challenging business problems as a data science problem and concrete set of tasks.
• Manages backlog well. Delivers projects to maximize business impact that are in-sync with wider timing of the business.
• Is creative and persistent in the face of roadblocks.
• Exhibits knowledge of the organization's processes, objectives, and challenges and understands their impact on the business.

About Expedia Group 

Expedia Group (NASDAQ: EXPE) powers travel for everyone, everywhere through our global platform. Driven by the core belief that travel is a force for good, we help people experience the world in new ways and build lasting connections. We provide industry-leading technology solutions to fuel partner growth and success, while facilitating memorable experiences for travelers. Expedia Group's family of brands includes: Brand Expedia®, Hotels.com®, Expedia® Partner Solutions, Vrbo®, trivago®, Orbitz®, Travelocity®, Hotwire®, Wotif®, ebookers®, CheapTickets®, Expedia Group™ Media Solutions, Expedia Local Expert®, CarRentals.com™, and Expedia Cruises™.

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