1. Be interesting and strategic.
2. Be curious and innovative.
3. Show up: be accountable, take responsibility, get back up when you are down.
4. Initiate and focus on project-level impacts and opportunities.
5. Create interesting stuff
6. Tell stories using data and the analysis of that data.
7. Develop others, yourself, and the business.
8. Share so others can see what you’re creating.
9. Push the business to be better.

• Analyze sales, customer, and market research data specific to physical retail spaces, identifying trends, patterns, and insights that drive business decisions.
• Merge and correlate data from different sources, including sales, foot traffic, digital marketing, and customer feedback, to create a holistic view of retail performance and opportunities for optimization.
• Develop and implement advanced analytical models to predict customer behavior, sales trends, and the effectiveness of retail strategies.
• Collaborate with cross-functional teams, including marketing, sales, and operations, to ensure data insights are effectively integrated into business strategies.
• Lead the design and execution of A/B testing experiments to evaluate the impact of physical store changes on customer experience and sales.
• Present complex data findings in a clear and actionable manner to clients, senior management and stakeholders, supporting strategic decisions with data-driven evidence.

1. Champion a data-driven culture by promoting data literacy and providing training and resources across the organization.
2. Work closely with the data scientist and innovation lead on A.I. and machine learning initiatives.
3. Stay abreast of industry trends and advancements in data analytics, applying new techniques and technologies to continuously improve our analytical capabilities.
4. Mentor junior analysts and contribute to the development of the analytics team's skills and knowledge.
5. Stay current and connected to cultural and marketing trends.
6. Document everything thoroughly and elegantly – telling a story using data.
7. Create and maintain library of case studies, insights, trends and best practices.
8. Contribute to agency new business projects as needed.

• Experience in data analysis, with a significant portion focused on retail analytics or a closely related field is a plus.
• Strong proficiency in analytical tools and software, including SQL, Python, R, and data visualization tools such as DOMO, Tableau or Power BI.
• Demonstrated experience in analyzing and interpreting complex datasets, with the ability to translate data insights into strategic recommendations.
• Excellent problem-solving skills, with a proven ability to conduct high-level data analyses that inform business strategies.
• Strong communication and presentation skills, with the ability to articulate complex concepts to non-technical stakeholders.
• Ability to manage multiple projects simultaneously, with strong organizational and project management skills.
• Strong written and verbal skills, including the ability to prepare summaries and present to agency and client teams.
• Collaborative and a good team player. No jerks or prima donnas.
• A self-starter that likes to get things done, learn by doing, and show initiative.
• Organized, detail-oriented, able to multitask and still stay organized.
• Positive and professional: takes ownership of tasks and willingly takes on new responsibilities.
• Experience in A/B testing, predictive modeling, and statistical analysis techniques.

• A BA/BS in appropriate discipline such as analytics, statistics, mathematics, computer science, (recognized internationally) (MA/MS preferred but not required)
• Proven track record (5-7) years of experience in data management and analytics within a corporate or retail environment.
• Job Type: Permanent, Full-Time

Department: planning
This is a full time position