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.
This simple idea—that we all deserve to belong, and on our own terms—is core to who we are as a company and how we make decisions. Our teamis made up of thousands of people across the globe who take risks, think big, and do good for our customers, communities, and the planet. Ready to learn fast, create with audacity and lead boldly? Join our team.
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. Retail, supply chain management and/or logistics experience strongly preferred.
This hybrid opportunity is located in our beautiful San Francisco office.
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.
Guide discussion and empower more junior team members to identify best solutions.
Who You Are
Experience in developing advanced algorithms using machine leaning (ML), statistical, and optimization methods to enhance various business components in the retail sector.
Hands-on experience with forecasting models, running simulations of what-if analysis, and prescriptive analytics.
Experience with time series analysis, predictive modeling, hierarchical Bayesian, causal ML, and transformer-based algorithms.
Experience with creating business impact in supply chain, merchandise, inventory planning, or vendor management using advanced forecasting techniques.
Advanced proficiency in modern analytics tools and languages such as Python, R, Spark, SQL.
Advanced proficiency using SQL for efficient manipulation of large datasets in on prem and cloud distributed computing environments, such as Azure environments.
Ability to work both at a detailed level as well as to summarize findings and extrapolate knowledge to make strong recommendations for change.
Ability to collaborate with cross functional teams (Product, Engineering, etc.) and influence product and analytics roadmap, with a demonstrated proficiency in relationship building.
Ability to assess relatively complex situations and analyze data to make judgments and recommend solutions.
Mid-level career experience 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
Benefits at Gap Inc.
Merchandise discount for our brands: 50% off regular-priced 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 employee’s base pay.*
Gap Inc. is an equal-opportunity 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 long-held 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: $170,200 - $225,600 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.
US CandidatesPlease note that effective, June 30, 2022, Gap Inc. will no longer require any of its employees to wear face masks or require proof of COVID vaccination, unless required by local or state/provincial mandates or as part of Gap Inc's quarantine guidelines after being exposed to or testing positive for COVID. Therefore, please disregard any language in any job posting that refers to Gap Inc.'s face mask and proof of vaccination policy as said policy is no longer effective.