At a Glance
- Tasks: Analyse data to improve marketing strategies and drive growth for global travel brands.
- Company: Join Expedia Group, a leader in travel tech, making journeys smoother for everyone.
- Benefits: Enjoy flexible work options, travel perks, generous time-off, and career development resources.
- Why this job: Be part of a vibrant team shaping the future of travel with innovative analytics.
- Qualifications: PhD, Masters, or Bachelors in Mathematics or related field; 4+ years in data analytics.
- Other info: Recognised as a Best Place to Work by Glassdoor in 2024.
The predicted salary is between 42000 - 84000 £ per year.
Expedia Group brands power global travel for everyone, everywhere. We design cutting-edge tech to make travel smoother and more memorable, and we create groundbreaking solutions for our partners. Our diverse, vibrant, and welcoming community is essential in driving our success.
Why Join Us? To shape the future of travel, people must come first. Guided by our Values and Leadership Agreements, we foster an open culture where everyone belongs, differences are celebrated, and we know that when one of us wins, we all win. We provide a comprehensive benefits package, including exciting travel perks, generous time-off, parental leave, a flexible work model, and career development resources, all to fuel our employees' passion for travel and ensure a rewarding career journey.
Introduction to team: The Traveler Business Team builds and drives growth for our global consumer businesses—Expedia, Hotels.com, and Vrbo. This division creates compelling and differentiated traveler value for each brand by setting the strategic vision, operating strategy, and plan. Responsibilities include investment allocation, prioritization, P&L accountability, and leading cross-functional teams across Expedia Group, who are all held accountable to a single scorecard. The Marketing Measurement Analytics team is an integral part of the Traveler Business Team. They are looking for a high-performing individual contributor responsible for maintaining and improving Marketing Mix Model (MMM) operations and sign-off, ensuring they are business-ready.
If you are someone who consistently applies and enhances analytics capabilities, best practices, and processes to solve complex business issues and identify opportunities, then this could be the role for you!
In this role you will:
- Extract data from multiple sources and combine into required datasets for model building or analytics.
- Challenge MMM concepts and outputs based on specific modelling, marketing, and business knowledge.
- Collaborate with subject matter experts and stakeholders to clarify business questions and enhance feature selection.
- Apply probability, frequentist vs Bayesian statistics, and statistical concepts like regression, ANOVA, AB testing.
- Select appropriate measurement techniques/designs to answer business questions and explain trade-offs.
- Define and build data models, interpret outputs, and iterate to improve models.
- Provide guidance and coaching on statistical techniques.
- Understand common data models, their assumptions, and best data sources.
- Learn new modelling approaches and critically evaluate their benefits.
- Refine modelling project questions, drive model design decisions, and provide recommendations.
- Deliver iterative project steps, refine requirements, and evolve based on learnings.
- Create data pipelines and workflows, considering legal implications.
- Create shareable code and documentation.
- Develop clear visualizations to support data stories.
- Apply inclusive design principles to visualizations.
- Use common charting packages in scripting languages and seek alternatives when needed.
- Provide constructive feedback to upskill teammates.
- Build trust and collaborate transparently with stakeholders.
- Articulate project goals, methodology, caveats, and conclusions to technical and non-technical audiences.
- Present insights clearly and concisely, seeking feedback and actioning it.
- Create relevant artifacts like technical documentation, presentations, and executive summaries.
- Understand the organization's processes, objectives, and challenges.
- Work with big data, explaining challenges and solutions to partners.
- Write advanced SQL and understand different SQL flavors and querying tools.
- Know important data sources and support channels to resolve data issues.
- Use best practices for data quality checks and query optimization.
- Write shareable, efficient code for data pipelines.
- Adopt and evaluate new querying tools and datasets.
- Frame complex business problems as analytics problems and break them into manageable tasks.
- Work with stakeholders and analytics peers to identify the right objective and propose solutions appropriate for the task and timeframe.
- Demonstrate iterative thinking and identify next steps based on findings.
- Pick analytically valid approaches, favoring iterative delivery that solves for the objective, not just the ask.
- Communicate regularly with stakeholders, addressing problems and meeting key deadlines.
- Proactively resolve problems, identify opportunities, and collaborate with team members.
- Automate repeated measurement and reporting tasks, build scalable dashboards, and train stakeholders.
- Identify and reach out to relevant domain experts and stakeholders to maximize impact.
Experience and qualifications:
- PhD, Masters, or Bachelors (preferably in Mathematics or Scientific degree).
- 7+ years of work experience OR 4+ years in a comparable data analytics role.
- Experience delivering data-driven insights and recommendations through multiple projects.
- Advanced experience using R, Python, or SQL for data analysis, structuring, transforming, and visualizing big data.
- Experience delivering analytics projects to different business areas with strong business acumen.
- Understanding of MMM & incrementality testing techniques.
- Critical thinking, problem-solving, communication, influencing, information gathering, listening, and statistics skills.
- Data visualization skills for communicating results to stakeholders of different technical levels.
- Basic machine learning concepts and approaches.
Accommodation requests: If you need assistance with any part of the application or recruiting process due to a disability, or other physical or mental health conditions, please reach out to our Recruiting Accommodations Team through the Accommodation Request.
Expedia Group is committed to creating an inclusive work environment with a diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, gender, sexual orientation, national origin, disability or age.
Advanced Data Insights Analyst III (Marketing Analytics) employer: ENGINEERINGUK
Contact Detail:
ENGINEERINGUK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Advanced Data Insights Analyst III (Marketing Analytics)
✨Tip Number 1
Familiarise yourself with Marketing Mix Models (MMM) and incrementality testing techniques. Understanding these concepts will not only help you in interviews but also demonstrate your commitment to the role and its requirements.
✨Tip Number 2
Brush up on your SQL skills, especially advanced querying techniques. Since the role requires writing efficient code for data pipelines, showcasing your proficiency in SQL during discussions can set you apart from other candidates.
✨Tip Number 3
Prepare to discuss your experience with data visualisation tools and how you've communicated complex data insights to non-technical stakeholders. This is crucial for the role, as you'll need to present findings clearly and concisely.
✨Tip Number 4
Network with professionals in the travel and tourism sector, particularly those involved in analytics. Engaging with industry experts can provide valuable insights and potentially lead to referrals, increasing your chances of landing the job.
We think you need these skills to ace Advanced Data Insights Analyst III (Marketing Analytics)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the job description. Focus on your analytical skills, experience with data visualisation, and any specific tools mentioned like R, Python, or SQL.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data analytics and travel. Mention specific projects where you've applied statistical techniques or delivered insights that drove business decisions, showcasing your problem-solving abilities.
Showcase Your Technical Skills: Clearly outline your technical skills in your application. Include examples of how you've used advanced SQL, created data pipelines, or developed dashboards. This will demonstrate your capability to handle the responsibilities of the role.
Prepare for Potential Assessments: Be ready for possible assessments or tests related to data analysis or coding. Brush up on your statistical knowledge and be prepared to discuss your approach to solving complex business problems using data.
How to prepare for a job interview at ENGINEERINGUK
✨Showcase Your Analytical Skills
Be prepared to discuss your experience with data analysis, particularly in relation to Marketing Mix Models (MMM). Highlight specific projects where you applied statistical techniques like regression or ANOVA, and be ready to explain your thought process and the outcomes.
✨Demonstrate Collaboration
Since this role involves working with cross-functional teams, share examples of how you've successfully collaborated with stakeholders. Discuss how you clarified business questions and enhanced feature selection through teamwork, as this will show your ability to work well within a diverse environment.
✨Prepare for Technical Questions
Expect technical questions related to SQL, R, or Python. Brush up on your coding skills and be ready to demonstrate your ability to write efficient queries or scripts. You might also be asked to explain your approach to data quality checks and optimization.
✨Communicate Clearly
Practice articulating complex data insights in a way that is understandable to both technical and non-technical audiences. Prepare to present your findings clearly and concisely, and be open to feedback during the interview, as effective communication is key in this role.