Summer 2022 Data Science and Digital Analytics Intern
At Bath & Body Works our Digital Analytics and Data Science team drives the understanding of our eCommerce business. This understanding is fueled by insights into customer behavior and driving optimal customer interaction. The analytics and data science team contribute to key business initiatives with partners throughout the organization such as marketing, site merchandising and UX.
Our 10-week internship experience will provide a comprehensive learning experience in the areas of data and analysis with additional insights into eCommerce performance within a fast paced, innovative retail brand.
- Integrated in the program are opportunities to research and propose actionable findings to the business that are customer centric and focused on driving growth within the brand.
- Develop analyses to drive deeper understanding of customer behavior, marketing investment and site optimization
- Analyze consumer behavior and customer journey to inform enhancements and optimization
- Research trends in analytics and data science to help develop new ways of reviewing business performance
- Build predictive models using customer and demand data to determine key business drivers
- Participate in Bath & Body Works intern development activities
- University undergraduate or graduate student majoring in Computer Science, Business Informatics, Statistics, Mathematics or related field
- GPA must be at least a 3.0
- Programming knowledge and skills, experience with statistical programming software (i.e. R, Python), and knowledge of database query languages (i.e. SQL)
- Innate curiosity and desire to learn, strong analytical and logical thinking skills
- Ability to identify solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets
- Excellent verbal and written communication skills and the ability to interact professionally with diverse groups, executives, managers, and subject matter experts
- Knowledge of statistical forecasting and machine learning concepts (i.e. decomposition, linear regression, exponential smoothing, support vector machine, k-means clustering, boosted decision-tree)
- Able to work in a fast-paced environment
- Have a strong passion for retail