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Axis Capital

Global specialty insurance and reinsurance provider

Data Science & AI Delivery Lead

Applied Machine LearningConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • Demonstrable professional experience delivering AI and machine-learning solutions, with a track record of taking projects from concept through production.
  • Expert-level Python proficiency and experience with core data science and machine-learning libraries such as scikit-learn, pandas, PyTorch, or TensorFlow.
  • Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark-based data processing.
  • Familiarity with generative AI concepts and tooling, including large language models, prompt engineering, retrieval-augmented generation patterns, and vector search.
  • A solid understanding of MLOps principles, including CI/CD for models, automated testing, and monitoring deployed solutions.
  • Cloud platform experience, preferably Azure, including services such as Azure OpenAI, Azure Machine Learning, or Azure AI Search.
  • Experience managing or leading technical delivery teams while remaining hands-on, with a track record of fostering a positive, high-performing team culture.
  • Strong project management skills, including resource estimation, progress tracking, and meeting deadlines in a fast-paced, multi-priority environment.
  • Excellent communication skills and the ability to translate complex technical concepts for business stakeholders.
  • Ability to operate independently and step into a leadership vacuum when needed.

Responsibilities

  • Own the operational running of AI delivery workstreams, ensuring the team is focused, unblocked, and delivering against priorities; act as the primary point of escalation when the Head of is unavailable.
  • Own technical execution across AI delivery workstreams; lead architectural decisions, technical design reviews, implementation approaches, and production readiness reviews; establish engineering standards, patterns, reusable frameworks, and delivery best practices.
  • Own technical delivery accountability from concept through production and ensure solutions meet security, governance, scalability, explainability, and operational support standards.
  • Provide technical guidance on solution design, model selection, and architecture decisions.
  • Review code and technical outputs to maintain quality standards, and contribute hands-on to Python-based development when needed, particularly during critical delivery phases or proof-of-concept work.
  • Support the design and delivery of generative AI solutions, including retrieval-augmented generation architectures, prompt engineering, and integration with Azure AI services such as Azure OpenAI and Azure AI Search.
  • Ensure robust MLOps practices, including model versioning, testing, deployment pipelines, and monitoring deployed solutions for performance and drift.
  • Champion engineering best practices across the team, including code review standards, documentation, version control with Git, and separation of experimentation from production-ready code.
  • Own AI solution architecture and technical design standards; define engineering approaches for large language model applications, agentic systems, machine-learning solutions, and AI platforms.
  • Lead evaluation of emerging AI technologies and determine appropriate adoption; establish standards for MLOps, AI observability, model lifecycle management, and responsible AI implementation.
  • Work with Business Technology Solutions on solution architecture and delivery, and with the Program Office on delivery planning, timelines, cost estimates, and status updates.
  • Partner with Data Engineering to ensure data pipelines and lakehouse structures support AI delivery needs.
  • Support the Head of Data Science & AI Delivery in leading and developing a growing team of Data Scientists and AI Engineers; mentor and coach team members through hands-on pairing, structured code reviews, and knowledge-sharing sessions.
  • Provide hands-on coaching through architecture reviews, code reviews, pair programming, model reviews, and technical mentoring while remaining actively involved in delivery.
  • Support the Head in tracking the project pipeline, estimating costs including cloud computing and API consumption, and managing resource allocation against priorities.
  • Stay current with new foundation models, open-source frameworks, vector databases, orchestration tools such as LangChain and Semantic Kernel, and evaluation methodologies; bring ideas to the team and lead proof-of-concept development to assess feasibility and value.
  • Represent the Head of Data Science & AI Delivery in meetings, steering groups, and stakeholder forums as required.
  • Attend the local office at least three days per week and engage in company activities to build colleague relationships and team culture.

Desired Qualifications

  • Experience with advanced natural language processing techniques beyond prompt engineering, including fine-tuning and evaluation frameworks for generative models.
  • Experience working in the insurance or reinsurance industry, with an understanding of underwriting, claims, or actuarial data.
  • Knowledge of responsible AI practices, including bias detection, explainability, and fairness testing.

About the Company

Axis Capital

Global specialty insurance and reinsurance provider

Axis Capital operates as a global specialty lines insurer and reinsurer. It provides tailored insurance and reinsurance solutions to clients across various industries, leveraging its expertise in specialty lines to deliver comprehensive coverage. The company works by offering customized risk-transfer products through a global network of 19 offices and strategic partnerships, supported by strong financial strength and high credit ratings to manage risk effectively. Its differentiators include a solid balance sheet, durable financial ratings, and a global presence that enables it to serve a diverse client base and adapt to market changes. The goal is to provide reliable, customized risk solutions for clients worldwide while maintaining financial stability and building strategic partnerships to navigate evolving market conditions.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Hamilton, TX
Founded
2001

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