Role Overview

At Levi Strauss & Co, we are revolutionizing the apparel business and redefining the way denim is made. We are taking one of the world’s most iconic brands into the next century through innovations like machine learning-powered denim finishes, block-chain for worker wellbeing, and algorithms to optimize our supply chain and meet consumer needs.

You will join our global Data, Analytics & AI team to create advanced analytics, machine learning, and AI solutions. You will translate stakeholder needs into predictive models and actionable insights to drive revenue and/or reduce cost, focusing on automation and business process improvement.

Responsibilities

Develop analytical solutions / production-ready models that solve pricing and promotions problems, taking account of business needs and technology/operations landscape.
Apply advanced analytics, machine learning, and AI techniques to derive business value from the full range of internal and external data sets, leveraging Cloud-based technology.
Actively collaborate on the development of pricing elasticity modeling, pricing recommendations, promotional campaigns optimization and discounts recommendations.
Translate complex data and methodology into strategic, operationally feasible insights and recommendations.
Communicate clearly and effectively to technical and non-technical audiences, verbally and visually, to create understanding, engagement, and buy-in.
Identify trends and opportunities to drive innovation, both in what we do and how we do it.
Document all code and approach; actively contribute to and re-use community best practices.
Be a great team player who embodies the values and passions that characterize Levi Strauss; have empathy to engage with colleagues from a wide variety of backgrounds.

Requirements

Advanced Degree in Mathematics, Physics, Computer Science, Engineering, Statistics, or an equivalent discipline required.
7 to 10 years of experience in developing models and algorithms in a commercial environment with a track record of creating meaningful business impact.
Strong SQL and Python skills required; proficiency in at least one open-source programming language desirable.
Proficiency with data visualization tools (Looker, Streamlit, Tableau or similar).
Experience with native ML orchestration systems such as Kubeflow, Vertex AI Pipelines, Airflow.
Proficiency with Spark.
Expertise in standard software engineering methodology, e.g. unit testing, test automation, continuous integration, continuous deployment, code reviews, design documentation.
Experience implementing and optimizing Large Language Models (LLMs) for business applications.
Experience working in agile methodology.
Prior experience in retail or FMCG.
Expertise in multivariate statistical modelling (e.g. clustering, regression, principal components and factor analysis, time-series forecasting, Bayesian methods) and machine learning (Random Forest, KNN, SVM, boosting and bagging, regularization etc.) required.
Experience with cloud computing platforms (GCP, AWS or other).
Ability to simultaneously coordinate and track multiple deliverables, tasks and dependencies across multiple stakeholders / business areas.