Job Title 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 client 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 ability to adapt and expand successful analytical solutions as well as finance sector background supporting retail analysis and portfolio planning. Job Description Key Responsibilities : - Skilled at working with diverse stakeholders to quickly understand the key drivers of their business , with focus on 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 collaborative, inclusive, engaging, inquisitive, and creative demeanour Experience Required - Bachelor's degree in Business, Accounting, Math, Statistics, Computer Science, Finance, Economics, or 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 different 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.