Job purpose: Lead and assist cross-functional & cross-regional teams to provide data analysis, monitoring, and forecasting, creating the logic for and implementing strategies, providing requirements to data scientists and technology teams on attribute, model, and platform requirements, and communicating with global stakeholders to ensure we deliver the best possible customer experience.

Accountabilities:

- Work cross-functionally with teams to analyze usage and uncover key, actionable insights about customer behavior. Identify opportunities where scientific techniques can be applied to solve business problems

- Expert use of current and emerging technologies to evaluate trends and develop actionable insights and recommendations to management, via an understanding of the business model and the information available for analysis

- Leads staff in the most advanced descriptive, diagnostic, predictive, prescriptive, and ensemble modeling, advanced statistical techniques, use of database tools and/or other approaches in quantitative analysis of complex business situations

- Designing and measuring controlled experiments to determine the potential impact of new approaches. Help with various data analysis and modeling projects

- Place actionable data points and trends in context for leadership to understand actual performance and uncover opportunities. Take ownership of the end-to-end system from Problem statement to Solution Delivery and leverage other teams if required

- Research and implement best practices to improve the existing decision science infrastructure. Stay up to date on burgeoning decision science developments that may affect our business going forward

- Mentors less senior staff. Lead cross-functional projects and programs formally preparing and presenting to management. Routinely work on multiple highly complex assignments concurrently

- Provides consultation to Sr. Leadership on a normal basis

Qualifications & Specifications:

- Master's degree in computer science, engineering, statistics, economics, or equivalent

- Proven ability to use modeling, optimization, machine learning, or text classification algorithms

- Possess a background in database design, ETL processes (SSIS), and SQL analysis (SSAS) to assist the Analytics team in formalizing their internal data flows and related reporting processes

- Data virtualization, analytics, and integration techniques

- Technology Prowess in R/Python/SAS/SQL/ R Shiny and other self-service tools (KNIME/Dataiku etc). Experience in AI/ Machine Learning, real-time analytics, and Big data platforms

- Cloud Platforms - AWS, Google, or Azure

- Ability to lead, working collaboratively and creatively with business stakeholders

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