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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Director, Data Science - Agent-Led Engagement - **Company:** NEXT COMMERCE LLC - **Location:** Fremont, CA, United States - **Experience:** Experienced - **Salary:** $169,000.0 - $338,000.0 - **Contract:** Permanent contract - **Skills:** Adobe Analytics, Web Accessibility, Data Analysis, Application Frameworks, Python (Programming Language), Machine Learning, Tensorflow, Scala (Programming Language), Unstructured Data, Web Content Accessibility Guidelines, Reinforcement Learning, Large Language Models, Apache Spark, Agentic-AI, Scikit Learn, Information Technology, Build Tools - **Published:** October 8, 2026 - **Apply:** https://www.themuse.com/jobs/walmart/director-data-science-agentled-engagement-in-conversational-commerce-dbcf3c ## About the Role * 8+ years of experience in data science or applied machine learning * 5+ years leading teams developing ML-powered customer engagement or personalization systems * Deep knowledge of large language models (LLMs) and their use in dialogue, decisioning, and personalization * Experience combining LLMs with traditional ML approaches for behavioral modeling or targeting * Expertise in building user profiles from structured and unstructured data, and using them for recommendation or ranking * Proven ability to build systems that personalize interactions based on customer history and real-time signals * Strong communication skills, with the ability to drive clarity across engineering, product, and experience teams Preferred Qualifications * Advanced degree in Computer Science, Machine Learning, or a related field * Experience in conversational commerce, personalized assistants, or task-oriented dialog systems * Familiarity with long-context LLM applications, memory architectures, and personalization infrastructure * Knowledge of reinforcement learning or contextual bandits applied to engagement optimization * Demonstrated ability to launch ML-powered product features that improved engagement, retention, or satisfaction, Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 6 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field. Option 3: 8 years' experience in an analytics or related field Preferred Qualifications... Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications. Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart's accessibility standards and guidelines for supporting an inclusive culture. ## Description Walmart's Next Gen Commerce team is redefining how customers shop by building intelligent, conversational agents that go beyond answering questions, they initiate value-driven conversations. As Director of Data Science for Agent-Led Engagement in Conversational Commerce, you will lead a core pillar under the Senior Director of Data Science - Agentic AI for Conversational Commerce. Your mission is to develop models that help the agent identify high-value moments to engage, suggest new topics, and continue conversations in meaningful, personalized ways. These proactive behaviors will be grounded in a deep understanding of each customer, drawing from both traditional digital signals (clicks, searches, orders) and conversational context. You will lead a team that builds decision systems combining traditional machine learning with large language models (LLMs). Your approach will include modeling short-term context from active conversations and maintaining long-term customer memory based on evolving profile attributes. Designing how this long-term memory is built, stored, and updated is critical to delivering truly personalized, proactive conversations. This is a hands-on leadership role. You will work closely with engineering, product, and experience teams to move fast, deliver with precision, and ensure technical solutions translate to measurable customer impact. Success in this role requires strong judgment, a bias for action, and the ability to work efficiently across functions in a highly iterative environment. Responsibilities * Lead and grow a team of applied scientists focused on proactive engagement within the conversational agent * Develop models that identify opportunities to initiate or extend conversations based on user behavior and intent, * Build systems to suggest relevant topics, journeys, or actions, grounded in customer history and ongoing conversation * Combine LLMs with traditional ML to model both short-term context and long-term memory for personalization * Define strategies for building, storing, and evolving customer profiles as persistent memory for LLM-based decisioning * Partner with product and UX teams to surface proactive suggestions in a natural, timely way during conversations * Establish and track metrics for engagement, relevance, and long-term customer impact * Align with other data science pillars to ensure consistency in agent behavior, quality, and personalization