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Manager Engineering Data Science

🌐 Remote💼 Full-time🗓 2026-07-24

Core

Lead a team building LTK's native AI platform and conversational AI capabilities, focusing on recommendations, retrieval, ranking, and semantic understanding.

Role type

Manager, Engineering - Data Science

Builds

LTK's AI platform, LLM-powered workflows, and productionized AI systems for user experience and business outcomes.

Domain

E-commerce / Social Commerce / Applied AI

Deliverable

production ML models | product features

Required skills

Machine learning, recommendation systems, ranking, retrieval, NLP, experimentation, applied statistics, Python, SQL, agentic AI, LLMs, advanced RAG, workflow-based AI systems

Preferred skills

Marketplace or social commerce experience, large-scale or real-time data systems experience

Technologies

AWS, GCP, Azure

Responsibilities

Lead a team of data scientists, drive development of AI native platform and LLM workflows, partner with engineering to productionize models, hire and develop talent, manage team performance

Seniority

Manager, hands-on leadership

Rewrite
## About the role We are hiring a Data Science Manager to lead a team building LTK's native AI platform and conversational AI capabilities across the company. This team will work on AI systems that power recommendations, retrieval, ranking, semantic understanding, and conversational experiences. We are looking for someone who can lead a team of data scientists, stay close to the technical work, and drive execution from idea to production. You will partner closely with engineering, product, and brand teams to turn business problems into scalable AI solutions that improve user experience and business outcomes. A key part of this role is building a high performing team. That includes setting clear expectations, giving direct feedback, coaching team members, and managing performance. ## How you will make an impact - Lead a team of data scientists building LTK's AI platform and conversational AI experiences. - Drive the development of LTK AI native platform and LLM powered workflows while thinking about cost efficiency. Also, partner with engineering to productionize models and build reliable AI systems. This includes providing technical guidance to teams on modeling, experimentation, evaluation, and production readiness. - Own team execution and help ensure features are delivered on time and at high quality. - Hire, develop, and retain strong data science talent. - Set clear expectations, provide regular feedback, and proactively manage the team's performance. ## What you will bring to LTK ### Data Science / AI - 7+ years of experience in data science, machine learning, or applied AI roles. - 3+ years of experience managing data scientists, or equivalent experience leading projects and mentoring others. - Experience building and deploying machine learning models in production. - Strong understanding of recommendation systems, ranking, retrieval, NLP, experimentation, applied statistics. - Experience with agentic AI, LLMs, advanced RAG, and workflow based AI systems. - Strong Python and SQL skills. ### Leadership / Execution - Ability to lead through ambiguity and keep teams moving in a fast-paced environment. - Experience driving projects from planning through execution while embracing AI coding assistant tools. - Strong ownership, prioritization, and follow through. - Comfort with direct conversations around accountability, growth, and team's performance. - Strong cross functional collaboration skills. ### Communication / Work Style - Strong written and verbal communication skills. Ability to explain technical concepts clearly to technical and non-technical partners. - Adaptability, moving with urgency, and a focus on operational excellence. - Growth mindset and openness to feedback. ### Technical Skills - Strong foundation in machine learning, statistics, and data analysis. - Experience with experimentation, model evaluation, and real world AI applications/systems. - Familiarity with cloud platforms such as AWS/GCP/Azure. - A bachelor's or master's degree in Computer Science, Statistics, Data Science, Engineering, or a related field is preferred, although relevant experience can substitute for formal education. ## Nice to have - Experience in marketplace, social commerce, or recommendation driven products. - Experience with large scale or real time data systems.
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