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88815BR

Title:

Data Scientist, Demand Forecasting

Location/Division:

NY-New York (Union Square)

Job Summary:

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.

Auto req ID:

88815BR

Employment Type:

Full-Time

State:

New York

City:

New York

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. Day to day you will:

• 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

Knowledge & Experience:

Success in this role requires high attention to detail, excellent analytical abilities, and strong business acumen. We’re seeking someone with:

• 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

Job Category:

Merchandising & Product Development

EEO Statement:

As an Affirmative Action Employer, Barnes & Noble hires qualified people to perform the many tasks necessary for the success of our business and is committed to diversity in the workplace. An essential part of this policy is providing equal employment opportunity for all. All employment practices and decisions—including those involving application procedures, recruitment or recruitment advertising, hiring, placement, job assignment, transfer, promotion, demotion, training, rates of pay or other forms of compensation, benefits, discipline, leave of absence, layoff, recall, termination and general treatment during employment—will be conducted without regard to age, race, color, ancestry, national origin, citizenship status, military or veteran status, religion, creed, disability, sex, sexual orientation, marital status, medical condition as defined by applicable law, genetic information, gender, gender identity, gender expression (including transgender status), hairstyle, height and/or weight, pregnancy, childbirth and related medical conditions, reproductive health decisions, or any other self-identified, perceived or actual characteristic protected by applicable federal, state, or local laws and ordinances.

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