Senior Manager, Business Performance Analytics
3 days ago
Senior Manager, Business Performance Analytics
Expedia is seeking a Senior Manager – Business Performance Analytics to join our team.
What you’ll do:
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.
An experienced professional capable of providing financial planning support to a business partner or finance team. A leadership figure dedicated to shared success and committed to achieving excellence, guiding both junior and senior analysts. Manages work across distinct domains and capability areas with clear guidance from senior management, collaborating with senior leaders and stakeholders. Aspires to foster a high-performing and efficiently managed team focusing on delivering high-quality results. Additionally, consistently offers constructive feedback and mentorship to enhance analytical skillsets within the immediate and broader team.
Who you are:
Masters or Bachelors degree with strong academic profile and emphasis on quantitative coursework (e.g., degree in Engineering, Mathematics/Statistics, Computer Science, Economics, Business Administration)
8+ years of experience in managing highly quantitative analytics projects, applying various statistical techniques in R/Python or Machine Learning techniques/tools to develop algorithms and predictive models
2-4 years of managing analytical teams
Experience with SQL, Hadoop/Hive, R, Python and Tableau
Exceptional data mining and quantitative analytic ability and hands-on data analytics experience
Track record in driving a data driven culture across business units
Excellent oral and written communication skills, and comfort presenting to everyone from entry-level employees to senior vice presidents
Relevant Experience:
Demonstrable experience in guiding and reviewing team's data-driven insights and recommendations to drive change or performance improvement for stakeholders through multiple projects using different analytics techniques
Strong business acumen and demonstrates knowledge of supervised machine learning theory and techniques; propagates the importance of being a valuable partner to Machine Learning Data Science to validate and scale models for optimal business value
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)
Expert understanding of complex 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). Mentors junior team members in this area and can help them identify subject matter experts across the business to consult.
Demonstrates a strong understanding of technical information to understand and synthesize different data sources and create basic data pipelines and workflows to support the model. Considers legal implications and seeks out clarification and solutions if applicable. Can identify blockers in these areas and suggest workarounds or transparently communicate limitations of the model.
Demonstrates the capability of framing a complex business problem as an analytics problem and concrete set of analytical tasks broken down into manageable chunks to reduce chaos
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.
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