Enterprise Data Product Analyst
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- 2+ Years of hands-on experience in Data Analytics with desire to grow into more strategic Product-oriented role
- At minimum has entry level experience in a multi-functional corporate setting – Retail specific experience is a plus
- Bachelor's or Master's degree from a reputable institution with some combination of focus in Retail relevant domains and either Traditional Statistics or Data Analytics background
- Passion for working in a fast-paced agile digital environment is a must!
- Prior exposure to agile product development processes is preferred
- Solid technical background with understanding and/or hands-on experience in following is a must:
- Quantitative Analysis & Programming (Python, R, etc.)
- SQL
- Data Modeling / Database Design
- IT Systems Analysis (Exposure to Both Cloud & Legacy Systems)
- Excellent analytical skills with an understanding of Web Analytics, engagement KPI's and a mature understanding of how to build business cases, measure benefits and communicate results to Sr. Leadership.
- Superior relationship building with cross-functional teams to deliver results through excellent partnership, communication and negotiating skills
- High level of attention to detail with the ability to work collaboratively across multiple teams, communicate effectively, adjust priorities based on business results, and work in a continuously changing environment to meet critical deadlines
- Strong strategic, creative thinking and decision-making skills
- Highly organized with the ability to multi-task and prioritize tasks to deliver expected results on time
- Must have extremely strong interpersonal skills and the ability to maintain and develop internal and external relationships; collaborating across multiple business and technology functions, relationship building and consensus building are essential
- Self-motivated and results oriented individual able to work independently and also work collaboratively with a team
- Excellent communication skills with the ability to interact with all levels of the organization, and communicate with technical and non-technical audience
- Experience and enthusiasm for testing, analyzing, and iterating on Enterprise Data Assets in order to enable Analytic success and improved self-service of insight
- Deep understanding of, and empathy for users