Senior Data Science Platform Lead — Remote (US)

LTK USA; Oregon; Hybrid; USD 150,000 - 190,000; Full time

Benefits offered by this job

401(k) with company matching

Medical Insurance

Paid Maternity/Paternity Leave

Summer Fridays

Flexible PTO

Job summary

LTK is seeking a Senior Data Science Manager to lead the team building its foundational AI capabilities. You will define the AI platform roadmap, driving shared capabilities across search, recommendations, catalog, and other product workflows.

You will coach a high-performing team, hire top talent, and partner with engineering to deliver reliable AI services. The role emphasizes hands-on technical leadership, platform ownership, and a focus on adoption, performance, and cost efficiency in

Qualifications

• 7+ years of experience in data science or ML.
• 3+ years of direct people management experience leading DS/ML teams.
• Experience shipping AI systems including production runtimes and observability.

Responsibilities

• Lead a Senior Data Science team to build foundational AI capabilities.
• Define the AI platform roadmap and prioritize shared investments.
• Deliver production-ready AI services and ensure reliability, latency, and cost efficiency.
• Collaborate with engineering and product teams to drive adoption and developer experience.
• Hire, coach, and grow team members, managing performance.

Skills

Data Science

Machine Learning

People Management

AI Systems Shipping

Eval Frameworks

Education

Bachelor’s or Master’s in CS/Statistics/DS

Tools

ML Platforms

Observability Tools

Job description

LTK is seeking a Senior Data Science Manager to lead the team building its foundational AI capabilities. You will define the AI platform roadmap, driving shared capabilities across search, recommendations, catalog, and other product workflows.

You will coach a high-performing team, hire top talent, and partner with engineering to deliver reliable AI services. The role emphasizes hands-on technical leadership, platform ownership, and a focus on adoption, performance, and cost efficiency in