Top AI & Machine Learning Jobs in Boston, MA

Lead a new AI-focused data science team accelerating insurance pricing program rollouts. Partner with pricing, delivery, and technology teams to identify AI opportunities; build evaluations for AI and agentic systems; define metrics, statistical tests, ground truth, and production experiments; measure value and risk; translate business needs into requirements; and prototype evaluation tools and AI applications. The role requires insurance pricing expertise, advanced statistics, strong Python and data science skills, modern LLM experience, and effective stakeholder communication.

Lead AI and data science efforts that accelerate insurance pricing program rollouts. Partner with pricing, delivery, and technology teams to identify AI opportunities, build evaluations for AI and agentic systems, define metrics and statistical tests, measure value and risk, and develop evaluation tooling and AI applications. Apply insurance pricing expertise, modern LLM experience, experimental design, and strong stakeholder communication to move high-value solutions into production.

Leads data science for medical and workers’ compensation claims, identifying AI/ML opportunities and delivering machine learning, GenAI, LLM, RAG, and agentic solutions. Partners with Claims, Technology, Product, Engineering, and UX teams to establish roadmaps, build intelligent systems, measure business impact and quality, implement MLOps practices, and mentor stakeholders. The role begins as a senior individual contributor and is expected to build a team.

Leads a new data science team developing AI and agentic-system evaluations for insurance pricing applications. Sets strategy, defines evaluation metrics and experiments, measures AI value and risk, partners with technical and pricing teams to deploy high-value solutions, and assesses third-party AI vendors. Requires strong people leadership, insurance pricing-model expertise, statistical and experimental-design skills, and hands-on experience with LLMs, RAG, and AI application development.

Leads data science strategy and execution for medical and workers’ compensation claims. Builds machine learning, generative AI, LLM, RAG, and agentic solutions; establishes roadmaps, evaluation metrics, monitoring, and operational practices; partners with claims, engineering, product, architecture, UX, and technology teams; and provides technical mentorship. Initially an individual contributor, the role is expected to build a team over time.

An 11-week data science internship involving research, data gathering and analysis, exploratory and regression analysis, model development and evaluation, and business recommendations. Interns work independently and collaboratively while developing skills in GenAI, machine learning, statistical modeling, and business analytics.

Develops AI and machine learning prototypes for insurance applications using Python, large language models, NLP, retrieval-augmented generation, agentic AI, information retrieval, and computer vision. Collaborates with data scientists and engineers on ideation, product design, algorithm development, data analysis, and experimentation in an R&D environment.