Data Scientist, Demand Forecasting

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About the position

We're seeking a highly skilled Data Scientist to join our team, with a focus on demand forecasting and supply planning. In this role, you will train and implement demand forecasting algorithms using modern machine learning techniques, driving measurable improvements in forecast accuracy. These demand forecasts will be used to support buying and replenishment decisions for all products in our stores and distribution centers. This is a critical role in driving business success. By developing and deploying advanced analytics solutions to inform inventory purchasing decisions, you will help ensure high stock availability while reducing our inventory investment. This is a hybrid position requiring 2-3 days in our NY office. An employee in this position can expect an annual starting rate between \$100,000 - \$120,000 depending on experience, seniority, geographic locations, and other factors permitted by law. What You Do The Data Scientist, Demand Forecasting role supports our buying teams with the key tools and information needed to run the business. You are instrumental in advancing our Demand Planning, analytical capability, data quality, and forecasting tools used by multiple internal B&N partners. This role will have a direct impact on our ability to improve forecast accuracy and drive business growth with optimized inventory levels.

Responsibilities

  • Develop and deploy demand forecasting models using machine learning and statistical techniques
  • Collaborate with IT to implement models in production, ensuring seamless integration with existing systems
  • Guide data engineering efforts to improve analytical capabilities, including data governance, quality, architecture, and tooling
  • Analyze large datasets to inform business decisions, identifying trends, opportunities, and challenges
  • Communicate complex technical concepts to non-technical stakeholders, providing actionable insights and recommendations
  • Stay up to date on changes in the field of forecasting, including the use of AI, to improve and scale forecasting capabilities

Requirements

  • A degree in Computer Science, Statistics, Mathematics, or related field
  • 3-5 years of experience in data science, with a focus on time-series analysis, regression analysis and machine learning
  • Strong technical skills in programming languages such as Python, R, and SQL
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn
  • Excellent leadership and collaboration skills, with experience working with cross-functional teams
  • Strong communication and presentation skills, with ability to distill complex concepts into actionable insights
  • Experience with cloud-based technologies and data engineering tools such as Databricks and Azure
  • Familiarity with agile development methodologies and DevOps practices
  • Knowledge of retail operations, merchandising and supply chain processes
  • Must be able to work our of our NY office 2 - 3 days/week
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