Retail PM&S Portfolio Planner

Retail PM&S Portfolio Planner

Job Description Summary

Cushman & Wakefield is seeking a Retail Portfolio Planner (Director of Data Science, Spatial & Predictive Modeling) to lead the development of unique innovative approaches to footprint optimization for finance sector clients to support their retail and quasi-retail requirements. You’re a great fit if you have experience partnering with business stakeholders to weave business objectives and internal data with third-party data to develop predictive or spatial models for action-oriented deployment. This role requires broad knowledge of data science techniques and the ability to adapt and expand successful analytical solutions, as well as a finance sector background supporting retail analysis and portfolio planning.

Key Responsibilities

• Skilled at working with diverse stakeholders to quickly understand the key drivers of their business, with a focus on the finance sector.
• Manage the development of frameworks analyses from simplistic to sophisticated predictive, spatial, and network optimization models to support the solutioning of business problems within the context of retail real estate.
• Expert at distilling complicated data science into plain language.
• Lead diverse project teams to ensure project success and effective team resource allocation while communicating with Senior team leaders.
• Lead efforts to drive scalable concepts and tools into the team’s core product kit.
• Leverage insights, collaboration, and delivery to ensure that we are the industry leader in product innovation.

Possess a collaborative, inclusive, engaging, inquisitive, and creative demeanour.

Experience Required

• Bachelor's degree in Business, Accounting, Math, Statistics, Computer Science, Finance, Economics, or a related field.
• 7-10 years progressive consulting and/or solution development experience required.
• Applicable understanding of commercial real estate practices strongly preferred.
• Finance sector experience preferred.
• Advanced analytical skills and techniques, including deep statistical knowledge, big data knowledge, visualization, and data exploration. Experience with R/Python and/or Alteryx preferred.
• Experience in the application of skills to develop a variety of model types to generate action-oriented outputs foundational to long-term client strategy.
• Ability to handle large amounts of data, identify key information, and provide insightful recommendations to all levels within the organization with minimal direction.