Director I, Data Science, Enterprise Data & Data Science

Liberty Mutual Fire Insurance Co.; United States; On-site; USD 150,000 - 230,000; Full time

Job summary

ApplyMint is seeking an exceptional Data Scientist with hands‑on experience in data science, MLOps, and GenAI to join our Enterprise Data & Data Science team. This full‑time remote role requires practical problem solving and cross‑functional collaboration across the business.

You will design and deploy GenAI solutions, build semantic layers and knowledge graphs, and create evaluation frameworks to ensure safety, reliability, and alignment with enterprise needs.

Qualifications

• Solid foundation in data science and ML fundamentals.
• Experience with MLOps across the full data science lifecycle.
• Proven ability to build GenAI solutions and agentic systems.
• Familiarity with GenAI evaluation methodologies.
• Experience with data semantic layers and knowledge graphs.

Responsibilities

• Design, build, and evaluate generative AI solutions and agentic systems.
• Develop data semantic layers and knowledge graphs for enterprise data accessibility.
• Build evaluation frameworks to assess GenAI performance, reliability, and safety.
• Collaborate with other data scientists, ML engineers, data engineers, and business partners.
• Champion best practices and tooling across a broad data science community.

Skills

Data science

Machine learning

MLOps

GenAI solutions

GenAI evaluation

Tools

Knowledge graphs

Semantic layers

Job description

Remote fromUSA Remote Posted 7 days ago

Full Time Executive Remote US

Description We’re seeking an exceptional, hands‑on Data Scientist with deep expertise in data science, MLOps, and building GenAI solutions to join our Enterprise Data & Data Science team. In this role

Key Highlights

• Design, build, and evaluate generative AI solutions and agentic systems
• Develop and maintain data semantic layers and knowledge graphs for enterprise-scale data accessibility
• Build evaluation frameworks and tools to assess GenAI systems’ performance, reliability, and safety
• Collaborate with other data scientists, machine learning engineers, data engineers, and business partners
• Champion best practices and tooling across a broad data science community

Preferred Qualifications

• Strong foundation in data science and machine learning
• Proven MLOps expertise across the complete data science lifecycle
• Experience building GenAI solutions and agentic systems
• Familiarity with GenAI evaluation methodologies
• Experience with data semantic layers and/or knowledge graphs
• Track record of cross-functional collaboration in a large enterprise environment