Data Scientist III, Analytics (B2B Supply Optimisation)

As a Data Scientist III, Analytics in our Analytics team, you will operate largely independently, applying and enhancing analytical best practices to solve sophisticated business problems. You will manage analytical workstreams, mentor junior colleagues, and engage regularly with stakeholders up to VP level.

Key Responsibilities

• Apply advanced statistical and machine learning techniques to supply optimisation challenges, delivering data-driven insights and recommendations that create measurable business impact.
• Extract, structure, and transform data from multiple sources independently to build datasets suited for modelling and in-depth analysis.
• Design and execute measurement frameworks—including A/B testing, causal impact analysis, and multivariate methods—selecting the appropriate technique based on the business question and clearly communicating trade-offs.
• Build, evaluate, and iterate on statistical models (e.g., regression, clustering, classification), correctly interpreting outputs and translating findings into actionable recommendations.
• Develop clear, audience-appropriate data visualisations and narratives that communicate insights to both technical and non-technical stakeholders.
• Lead small analytical workstreams end-to-end, partnering with stakeholders to refine requirements, agree on scope, and evolve the approach based on findings.
• Automate repeated measurement and reporting tasks and build scalable dashboards, enabling self-serve analytics for stakeholders across the business.
• Produce high-quality project artefacts—including technical documentation, presentations, and executive summaries—tailored to the appropriate forum and audience.
• Collaborate openly with analytics peers, domain experts, and business stakeholders to validate approaches, share knowledge, and socialise findings.
• Provide coaching and constructive feedback to junior team members on statistical techniques, visualisation best practices, and data quality standards.
• Champion reproducibility by writing shareable, well-documented code and contributing to shared repositories such as GitHub or Confluence.

Experience and Qualifications

• PhD, Master’s, or Bachelor’s degree in Mathematics, Statistics, Computer Science, or a related technical field; or equivalent related professional experience.
• 4–6 years of experience in a data science or analytics role (with a relevant degree), or 7+ years of comparable professional experience in a data analytics role.
• Demonstrable experience delivering data-driven insights that drove meaningful change or performance improvement across multiple projects using varied analytical techniques.
• Advanced proficiency in SQL, Python, or R for data extraction, transformation, and visualisation at scale.
• Proficient understanding of statistical concepts—including regression, ANOVA, probability, and frequentist vs. Bayesian approaches—and ability to distinguish statistically significant results from exploratory analysis.
• Experience applying a range of modelling techniques (e.g., linear and logistic regression, clustering) and iterating on models to improve accuracy and business relevance.
• Proficient communication skills, with demonstrated ability to present clear data stories and insights to audiences of varying technical levels.

Preferred Qualifications

• Experience in supply optimisation, pricing, marketplace analytics, or a related domain.
• Familiarity with big data querying tools such as Presto, Hive, BigQuery, or Hadoop.
• Exposure to Bayesian methods, causal inference, or multi‑armed bandit approaches.
• Experience collaborating with Machine Learning Data Science teams to validate and scale models for business impact.
• Familiarity with inclusive data visualisation design principles, including accessible colour selection and charting best practices.

If you need assistance with any part of the application or recruiting process due to a disability, please reach out to our Recruiting Accommodations Team.

Expedia 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.