Data Scientist II

About the Role

The Forecasting Team at Gap Inc. applies data analysis and machine learning techniques to drive business benefits for Gap Inc. and its brands. The team’s focus is to shape the company’s inventory management strategy through advanced data science and forecasting techniques. The successful candidate will lead the development of advanced forecasting models across various business functions, time horizons, and product hierarchies. Areas of expertise include forecasting, time series, predictive modeling, supply chain analytics, and inventory management. You will support the team to build and deploy data and predictive analytics capabilities, in partnership with GapTech, PDM, Central Marketing & business partners across our brands. This position is onsite in posted location.

What You\'ll Do

• Build, validate, and maintain AI (Machine Learning (ML) / Deep learning) models, diagnose, and optimize performance and develop statistical models and analysis for ad hoc business focused analysis.
• Develop software programs, algorithms and automated processes that cleanse, integrate, and evaluate large data sets from multiple disparate sources.
• Manipulate large amounts of data across a diverse set of subject areas, collaborating with other data scientists and data engineers to prepare data pipelines for various modeling protocols.
• Deliver sound, data-backed recommendations tied to business results, industry insights, and overall Gap Inc. ecosystem of technology, platform, and resources.
• Communicate compelling, data-driven recommendations as well as potential trade-offs, backed by data analysis and / or model outputs to influence leaders’ and stakeholders’ decisions.
• Build networks across the organization and partners to anticipate leader requests and influence data-driven decision making.
• Guides discussions and empowers more junior team members to identify best solutions.

Who You Are

Required

BS with 7+ years of experience (or MS with 5+ years) in Data Science, Computer Science, Machine Learning, Applied Mathematics, or equivalent quantitative field.

People mentoring experience, ability to work independently on large scale projects.

Proven ability to lead teams in solving unstructured technical problems to achieve business impact.

Full stack experience across analytics, data science, machine learning, and data engineering

Preferred

Retail experience

Supply chain management

Logistics experience

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