Introduction to team 

As the data-oriented business partners of finance, the Business Performance Analytics team will be an integral part of the Brands Finance organization. This team owns the performance metrics for the organization and drives the growth of Expedia Group and the optimization of marketing investments.
This individual provides finance support, analysis, and reporting. A leader committed to shared success and dedicated to excellence, offering immediate guidance to a compact team of junior analysts. Executes work on multiple well-defined projects with clear oversight from senior management, collaborating with senior leaders and relevant stakeholders.

In this role, you will:  

• Distill complex financial data into impactful insights; build financial models, analyze latest trends and initiatives, and perform ad-hoc modeling as required.

• Drive process improvement through effective business partnering across the organization.

• Responsible for forecast/outlook for a specific Brand(s) or EG-wide, including identifying and analyzing risks and opportunities.

• Lead a variety of projects to simplify and automate current processes

• Support Monthly/Quarterly Business Reviews, Board of Directors presentations, and Investor Relations /Earnings preparation.

• In-depth analysis and benchmarking of our portfolio of brands, the products we sell, and the marketing channels customers engage in as well as the external competitive landscape.

Experience and qualifications:  

• PhD, Masters or Bachelors (preferred for Mathematics or Scientific degree) with 6+ years of experience in data analytics with increasing responsibility

• Demonstrable experience in leading & delivering multiple projects with data-driven insights and recommendations that drove change or performance improvement for stakeholders

• Reviews the process of extracting data from multiple data sources and combining it into the required datasets for model building or analytics.

• Demonstrates awareness of intermediate supervised machine learning theory and techniques and displays a willingness to learn and apply to relevant projects and/or be a valuable partner to Machine Learning Data Science to validate and scale models for optimal business value

• Understand their teams need to collaborate with subject matter experts and stakeholders early in the process to clarify the business question, enhance the feature selection process, and select an output that is relevant to stakeholders.

• Uses business acumen in combination with the knowledge to appropriately guide teams in selecting the correct technique/design to answer business questions (eg. Pre/post, causal impact, multivariate, multi-armed bandit, etc)

• Good understanding of common data models, their underlying assumptions, the types of business questions they can best answer, and what data sources would best support the model (i.e. linear and logistic regression).

• Possesses an advanced understanding of the business domain and uses this to refine the question at the heart of the modelling project to drive model design decisions (i.e. model selection, feature engineering), and provide recommendations (model improvements, business changes, ab tests, further analysis etc)

• Demonstrates the capability of framing a complex business problem as an analytics problem and a concrete set of analytical tasks broken down into manageable chunks.

• Works with stakeholders and analytics peers to identify the right objective and propose solutions appropriate for the task and timeframe. Demonstrates iterative thinking and ability to identify next steps based on findings.