Data Scientist

About the Role The Customer Analytics Team at Gap Inc. applies data analysis and machine learning techniques to drive business benefits for Gap Inc. and its brands. The teams focus is on creating analytical capabilities to support customer acquisition, retention, personalization, and marketing at Gap Inc. Areas of expertise include segmentation, targeting, forecasting, marketing effectiveness measurement and optimizations, customer behaviors, site analytics, and business growth initiatives. You will support the team to build and deploy Data and Analytics capabilities in partnership with GapTech, PDM, Central Marketing, & business partners across our brands.

What Youll Do

• 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.
• 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.
• Communicate meaningful, actionable insights from large data and metadata sources to stakeholders.
• Be responsible for the quality of services and advice in meeting business partner needs.
• Be responsible for end results of the team and share responsibility over resources, budget, and adherence to policies.

Who You Are

• Advanced proficiency in R, Python, Spark, Hive, or other MR and common scripting languages for E2E pipeline.
• Advanced proficiency using SQL for efficient manipulation of large datasets in on-prem and cloud distributed computing environments such as Azure environments.
• Experience with ML and classical predictive techniques such as logistic regression, decision trees, non-linear regressions, ANN, CNN, boosted trees, SVM, Tensorflow, visualization packages, and a track record for creating business impact with these methods.
• 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.