- Enterprise Analytics is responsible for managing customer data, statistical modeling and advanced analytics requests for L Brands.
- The Data Scientist will be responsible for delivery of analytics requests and special projects. He / She will use several data sources and statistical techniques to interpret, analyze and develop solutions to business questions and present findings with actionable recommendations.
- Deliver projects around customer, marketing, merchandizing and inventory analytics and insights including ad-hoc requests originating from enterprise wide brands.
- Use various statistical techniques like but not limited to predictive modeling, customer profiling, segmentation, data mining etc. to provide relevant & accurate insights
- Execute predictive model scorings in order to support various customer marketing initiatives.
- Query structured/unstructured data and perform exploratory data analysis on customer data and provide actionable insights.
- Present ideas and findings with actionable recommendations in an easily consumable manner.
- Participate in peer reviews of projects
- Stay current with business results, strategies, industry standards and best practices.
- A degree in statistics / mathematics / economics / engineering / management with 5+ years of experience in statistical/quantitative analysis.
Lead Analyst / Data Scientist:
- 5+ years of experience in customer / marketing analytics role preferably in retail domain
- Expert level proficiency in SAS (Base SAS, Enterprise Guide, Enterprise Miner) or R and advanced SQL programming skills in a UNIX environment. Additional technical know-how of Python will be preferred
- In-depth knowledge of statistical procedures that are applied in segmentation, profiling, and data mining. Prior experience in machine learning techniques will be preferred.
- Experience in Excel, Excel-VBA and PowerPoint. Ability to automate insights / reports using Macros (SAS and Excel VBA) & other relevant technologies
- Experience in working with large relational databases (Teradata, Oracle). Prior experience in working on big data technologies will be preferred.
- Ability to understand business needs to generate relevant accurate insights or translate business needs into analytical specifications
- Demonstrated analytical & problem solving skills, ability to interpret reports, analyze trends and provide insights
- Strong written and verbal communication skills. Demonstrated ability to communicate complicated statistical analytical concepts to business stakeholders in a simplified comprehendible manner.
- Ability to mentor / train other analysts on the team
- Highly energized personality with a positive attitude and ability to work with minimal supervision, prioritize, multi task and work under tight timelines
- Advanced degree in Mathematics, Advance statistics, physics, operations research, bio statistics &/or computer science preferred but not required
- Technically proficient & relevant work experience in R/Python and other big data technologies (Manta, Hadoop, Aster Data) will be MANDATORY.
- Ability to mentor / train other data scientists & analysts on the team.