At a Glance
- Tasks: Use machine learning to solve marketing challenges and optimise revenue.
- Company: Join Tripadvisor Group, a leader in travel information and experiences.
- Benefits: Enjoy personal development opportunities, social activities, and access to industry conferences.
- Other info: Collaborative environment with diverse teams and excellent career growth potential.
- Why this job: Make a real impact on travel decisions for millions while growing your skills in AI.
- Qualifications: PhD or Masters in relevant field, strong ML background, and Python proficiency.
The predicted salary is between 63000 - 77000 £ per year.
The Tripadvisor Group Machine Learning Team is looking for an experienced individual to join a dynamic and fast-paced team to help support our Marketing efforts.
As an ML II Scientist, you will apply your modeling skills to a wide variety of problem spaces including, but not limited to bidding for online advertising, customer modeling, experimental design, revenue optimization, attribution, recommendations, life time value.
You will have access to the newest development tools and huge data sets.
You will deploy your solutions online and be able to observe the impact of your work in real time as you help the company grow.
Tripadvisor Group comprises Tripadvisor, the world's leading travel information site, and Viator, the leading marketplace for travel experiences.
The ML Team creates systems that influence the travel decisions of millions of people per day.
We apply cutting edge machine learning techniques to a wide variety of areas.
To ensure continued success, Tripadvisor promotes a culture of personal development, including social activities, journal clubs, memberships in online learning resources, and participation in industry conferences.
Have a great time while shaping the future of travel!
What You'll do: We are looking for someone who is independent, curious, and motivated, who likes discussing ideas and will bring something new to the table.
You will be working in a diverse environment where you'll collaborate with a broad multidisciplinary team of data scientists, analysts, software engineers, and product managers.
You'll be encouraged to take ownership of your projects and to find new opportunities and problems where machine learning could be applied to improve the business.
- Use machine learning models to solve a variety of core business problems across marketing.
- Seek out new opportunities to apply data science and machine learning in the marketing space across all channels (e. g., paid, organic, search, demand creation, affiliates, CRM…)
- Automate ETL pipelines
- Prototype, evaluate, deploy and maintain new ML models in production
- Design AB tests and analyze their results
- Discover new ways to analyze and interpret the data
- Communicate progress and interpretation of experimental results to technical and business stakeholders
Team player - Loves to learn
- Great communication skills with both technical and non-technical partners
- Gets things done on time and on specification
- Genuinely interested in AI - you've played with AI tools yourself, and you're excited to grow your skills in that space rather than waiting for it to be handed to you, Ph D or Masters in Computer Science, Engineering, Statistics, or related field preferred (or masters with 2+ years of practical experience)
- Knowledge of AB test design and analysis
- Strong background in machine learning and statistics
- Solid foundation on data structures and algorithms
- Proficiency in Python for numerical/statistical programming (our group relies heavily on Numpy/Pandas/Scikit-learn)
- Ability to interpret and write complex SQL queries
- Experience with big data technologies, such as Hive and Spark
- Track record of leading the deployment and maintenance of models
- Hands-on experience with AI-powered tools
We strive to create an accessible and inclusive experience for all candidates.
If you need a reasonable accommodation during the application or the recruiting process, please make sure to reach out to your individual recruiter or our team at Accessible Recruiting@tripadvisor. com.
The Tripadvisor Group connects people to experiences worth sharing, and aims to be the world's most trusted source for travel and experiences.
We leverage our brands, technology, and capabilities to connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories.
The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP), include a portfolio of travel brands and businesses, including Tripadvisor, Viator, and The Fork.
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Machine Learning Scientist- Mid-Level in City of Westminster employer: TripAdvisor
At Tripadvisor/Bókun, we pride ourselves on fostering a dynamic and inclusive work culture that empowers our employees to take ownership of their roles. As a Business Development Manager, you'll benefit from extensive professional growth opportunities, collaborative cross-functional teams, and the chance to make a significant impact in a rapidly expanding environment. Our remote work flexibility allows you to thrive while enjoying a healthy work-life balance, making us an exceptional employer for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Scientist- Mid-Level in City of Westminster
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We think you need these skills to ace Machine Learning Scientist- Mid-Level in City of Westminster
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at TripAdvisor, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at TripAdvisor. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at TripAdvisor
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at TripAdvisor!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
