Forecast Analyst – Python – Remote

The Forecast Analyst in the Demand Planning and Forecasting group will utilize advanced forecasting techniques to predict future sales. The role also requires development of new analytics, models, and simulations to take the organization to the next level. Highly team-oriented in nature, the ideal candidate is expected to work cross-functionally, demonstrating leadership in forecasting and inventory to partner with category management, marketing, global sourcing, product allocation, and purchasing. The candidate must be quantitatively adept, analytical, and demonstrate solid leadership skills.

Duties and Responsibilities

  • Responsible for the daily analysis and execution of forecast for all business channels
  • Create future forecasts for vendors to plan production
  • Develop forecast strategies for special events, seasonal items, and new item transitions
  • Identify, analyze, interpret and present trends or patterns in complex data sets by using Excel, SQL, Python, Tableau or similar.
  • Review forecasts, sales trends and advertising strategies to purchase and maintain appropriate inventory levels
  • Collaborate with other key departments to understand strategic directions and adjust forecasting inventory levels
  • Develop and utilize key management reports to monitor and identify areas of concern and areas where strategies are working well
  • Communicate regularly with multiple departments within the organization to align key strategies and identify and resolve supply chain issues
  • Guide and influence team members with adaption to new tooling, models and reporting.
  • Engage in continuous improvement initiatives
  • Additional duties as assigned by manager

Education (Required)

  • Bachelor’s Degree required

Skills (Required)

  • Strong knowledge/experience with reporting packages, programming and reporting (ie Tableau, Power BI, Python, SQL, etc.)
  • 1+ year experience in analytical and strategic field required (open to experience in reputable retailer, consulting, and/or finance)
  • Knowledge of statistics and experience using statistical packages for analyzing large datasets preferred.

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