Job Description

About Gap Inc.
Our brands bridge the gaps we see in the world. Old Navy democratizes style to ensure everyone has access to quality fashion at every price point. Athleta unleashes the potential of every woman, regardless of body size, age or ethnicity. Banana Republic believes in sustainable luxury for all. And Gap inspires the world to bring individuality to modern, responsibly made essentials.

About The Role
The Recommendations Data Science Team at Gap Inc. leverages advanced machine learning to power customer experiences across our digital platforms through personalized product recommendations. Our mission is to build scalable, productionready recommendation systems that support brand strategies and drive engagement and conversion for Gap Inc. and its family of brands. In this high impact role, you will build data pipelines and help to build and deploy deep learning models that power realtime personalization, optimize product ranking, and improve recommendation relevance across our digital platform. You will work closely with GapTech, Product Management, and business partners to ship recommendations optimizations that delight our customers.

What You'll Do

• Develop and deploy automated largescale ETL pipelines that power stateoftheart recommendation algorithms
• Collaborate with other data scientists in the team to assist in building AI (ML / Deep Learning) models, iterating on new experimental ideas, and building statistical approaches to evaluate model performance
• Manage unit testing and integration testing frameworks using pytest to ship bugfree code
• Build and maintain dashboards in GCP, Databricks, etc. to monitor the health of the deployed recommendation systems
• Collaborate with nontechnical teams such as Product and brands to translate model performance improvements into potential business impact

Who You Are

• Advanced proficiency using SQL, Python, and Spark for designing and maintaining data pipelines for model training and inference, with a focus on writing productionquality code
• Keen interest to work crossfunctionally across MLOps and Engineering to deploy models to production
• Experience with ML and classical predictive techniques such as logistic regression, decision trees, nonlinear regressions, ANN/CNN, boosted trees, SVM, visualization packages, and a track record for creating business impact with these methods
• Prior experience in applying deep learning techniques (using PyTorch and Tensorflow) and contextual bandits highly desirable
• Exposure to Azure, GCP, Databricks, Kubernetes, Cosmos, New Relic, Grafana a bonus

Benefits at Gap Inc.

• Merchandise discount for our brands: 50% off regularpriced merchandise at Old Navy, Gap, Banana Republic and Athleta, and 30% off at Outlet for all employees.
• One of the most competitive Paid Time Off plans in the industry.*
• Employees can take up to five on the clock hours each month to volunteer at a charity of their choice.*
• Extensive 401(k) plan with company matching for contributions up to four percent of an employees base pay.*
• Employee stock purchase plan.*
• Medical, dental, vision and life insurance.*
• See more of the benefits we offer.

Gap Inc. is an equalopportunity employer and is committed to providing a workplace free from harassment and discrimination. We are committed to recruiting, hiring, training and promoting qualified people of all backgrounds, and make all employment decisions without regard to any protected status. We have received numerous awards for our longheld commitment to equality and will continue to foster a diverse and inclusive environment of belonging. In 2022, we were recognized by Forbes as one of the World's Best Employers and one of the Best Employers for Diversity.

Salary Range: $109,600 - $137,000 USD
Employee pay will vary based on factors such as qualifications, experience, skill level, competencies and work location. We will meet minimum wage or minimum of the pay range (whichever is higher) based on city, county and state requirements.

Seniority level

• Entry level

Employment type

• Fulltime

Job function

• Engineering and Information Technology
• Retail

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