Senior Data Scientist, DTC

Job Location:  Multiple (Mexico, Brazil, Bolivia, Chile, Colombia, Peru) Calling all originals: At Levi Strauss & Co., you can be yourself — and be part of something bigger.   We’re   a company of people who like to forge our own path and leave the world better than we found it. Who   believe   that what makes us different makes us   stronger.   So   add your voice. Make an impact. Find your fit — and your future.   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: from creating machine learning-powered denim finishes to using block-chain for our factory workers' wellbeing, to building algorithms to better meet the needs of our consumers and optimize our supply chain.   Be a pioneer in the fashion industry by joining our global Data, Analytics & AI "startup with assets," where you will have the chance to build exciting solutions that will   impact   our global business across continents.   As a   Senior Data   Scientist   you will be a technical leader within the global Data, Analytics and AI team, driving the design and delivery of advanced analytics, machine learning, and AI solutions that address our consumers' needs while streamlining our processes and approaching the business in more innovative ways. This role will focus on applications of Data, Analytics, and AI to   DTC . Potential areas of application of AI include CLTV, CRM optimization, Segmentation,   Recommendations ,   Personalization   and Agentic   implementations   among others .   In this role, you will own the technical direction of key workstreams, influence the team’s roadmap, and serve as a bridge between data science and business stakeholders across regions. You will drive innovation, machine learning operationalization, adoption of data products, and data visualization / user interfaces / storytelling that put data at the center of our business. This role will aim to drive revenue and reduce   cost   through cross-region implementation,   automation   and business process improvement.   You will be expected to raise the technical bar across the team :   mentoring Data Scientists,   establishing   best practices, conducting code and model reviews, and contributing to the global Data, Analytics & AI community by sharing your knowledge and   leveraging   other colleagues’ experience in designing scalable, global solutions.   About the Job   Own and drive the technical direction   of multiple roadmap workstreams, from problem framing through production deployment, partnering with teams across the global organization.   Lead the design of complex ML/AI solutions   using advanced ML, deep learning, and generative AI techniques to solve high-impact retail and consumer problems.   Act as the primary technical point of contact   for business stakeholders on assigned workstreams ,   translating business problems into data science   solutions   and communicating results to non-technical audiences.   Mentor and coach   Data Scientist 1 and Data Scientist 2 team members,   providing   technical guidance on modeling approaches, code quality, and career development.   Conduct advanced statistical analysis to   provide   applicable insights,   identify   trends, and measure performance.   Build complex predictive models using ML, DL, and GenAI techniques with production-quality code and jointly own complex data science workflows with the Data Engineering and ML Engineering teams.   Define and enforce best practices   for model development, testing, documentation, and deployment within the team.   Scan the Data Science landscape for recent developments and proactively   identify   opportunities to integrate new methodologies into the existing project portfolio.   Contribute to architectural decisions   on the team’s ML/AI infrastructure, including model serving, feature stores, and observability.   Research best practices, conduct experiments, and build relationships with industry leaders and technology partners (e.g., Google, cloud vendors).   Ensure that the risks associated with projects are raised and mitigated to keep all projects on track.   Represent the Data Science team   in cross-functional forums, technical reviews, and vendor evaluations.   About You   Required Technical Skills   5+ years   of hands-on experience analyzing data and developing supervised and unsupervised models; including variable selection, feature engineering, model generation, model diagnostics, interpretability, and deployment.   5+ years   of experience writing complex SQL queries and working with large datasets in cloud/Hadoop-based environments. Experience writing   BigQuery   and   dbt   jobs.   5+ years   of experience with data visualization tools (D3.js, R Shiny, Looker, Tableau, or similar); able to   determine   the   appropriate visualization   for a variety of data types and create compelling stories with data.   5+ years   of experience deploying Machine Learning algorithms in a production environment.   3+ years   of experience developing Deep Learning based solutions for a production environment.   Experience with Generative AI and LLMs   — prompt engineering, RAG architectures, fine-tuning, and/or agentic AI frameworks (e.g.,   LangChain , Google ADK, or similar).   Experience working with different cloud services to develop ML solutions with   special   focus on Google Cloud Platform (Vertex AI,   BigQuery   ML, Cloud Run).   Expert-level Python, R, or similar programming skills.   Demonstrated experience mentoring   junior and mid-level data scientists.   Experience with experiment design and causal inference methods (A/B testing, uplift modeling, difference-in-differences).   Experience with distributed systems (Docker, Kubernetes, Kafka, or Spark).   Experience in Reinforcement Learning is a plus.   Des