LTK
Manager,Engineering-DataScience
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“Manager, Engineering - Data Science at LTK. Skills: Data Science, Machine Learning, AI Platform Development, Conversational AI, LLM, Team Leadership. 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”
Industry & Context.
turn business problems into scalable AI solutions
What They're Looking For.
Must Have
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, understanding of recommendation systems, ranking, retrieval, NLP, experimentation, applied statistics, Python and SQL skills, foundation in machine learning, statistics, and data analysis, Experience with experimentation, model evaluation, and real world AI applications/systems, A bachelor’s or master’s degree in Computer Science, Statistics, Data Science, Engineering, or a related field
Nice to Have
Experience in marketplace, social commerce, or recommendation driven products, Experience with large scale or real time data systems, Experience with agentic AI, LLMs, advanced RAG, and workflow based AI systems, Familiarity with cloud platforms such as AWS/GCP/Azure, relevant experience can substitute for formal education
What You'll Do.
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
Partner with engineering to productionize models and build reliable AI systems
Provide technical guidance to teams on modeling
and production readiness
Own team execution and help ensure features are delivered on time and at high quality
and retain data science talent
Set clear expectations
provide regular feedback
and proactively manage the team's performance
How You'll Work.
Team & Collaboration
Partner closely with engineering, product, and brand teams to turn business problems into scalable AI solutions; cross functional collaboration skills; Ability to explain technical concepts clearly to technical and non-technical partners
Communication Scope
written and verbal communication skills; Ability to explain technical concepts clearly to technical and non-technical partners
Process & Methodology
Drive projects from planning through execution
Full Job Description
LTK’s mission is to empower the world’s premium lifestyle Creators to achieve maximum economic success. We have a huge opportunity ahead of us and we’re looking for team members who want to create, innovate and disrupt an industry. We empower our team members to drive innovation, create value, and continue to spearhead the creation of this industry — a game changer when it comes to career growth. Position Title: Manager, Engineering - Data Science Location: Remote from the U. S. Reports to: VP of Applied AI, Search, and Catalog 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. W
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