Data Scientist II

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.

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.

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.   Experience working directly with cross-functional teams such as product management, engineers , business   partners.   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 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.     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