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About the Role

The Data Science & AI Delivery Lead is a key leadership role within the Data Science & AI Delivery team, acting as the deputy to the Head of Data Science & AI Delivery and ensuring the smooth day-to-day running of AI delivery operations. This role is critical for transforming business operations and leveraging AI advancements.

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.
• Directly manage the design, build, test, and deployment of AI solutions across multiple concurrent projects, ensuring quality and timely delivery.
• Provide technical guidance on solution design, model selection, and architecture decisions.
• Review code and technical outputs to maintain quality standards.
• 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 RAG architectures, prompt engineering, and integration with Azure AI services.
• Ensure robust MLOps practices are followed, including model versioning, testing, deployment pipelines, and monitoring of deployed solutions.
• Champion engineering best practices across the team, including code review standards, documentation, version control (Git), and a clear separation between experimentation and production-ready code.
• Work closely with AXIS's Business Technology Solutions for solution architecture and delivery.
• Collaborate with the Program Office for planning deliveries, providing 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.
• Foster a culture of excellence, collaboration, and continuous learning.
• Mentor and coach team members through hands-on pairing, structured code reviews, and knowledge-sharing sessions.
• Support the Head of in tracking the project pipeline, estimating costs, and managing resource allocation.
• Stay current with the rapidly evolving AI landscape, including new foundation models, open-source frameworks, vector databases, orchestration tools, and evaluation methodologies.
• Bring new 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.
• Take on additional duties, responsibilities, and activities appropriate to the nature of this role.

Requirements

• Demonstrable experience delivering AI/ML solutions in a professional environment, with a track record of taking projects from concept through to production.
• Strong technical knowledge, including proficiency in Python and experience with core data science and ML libraries (e.g., 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 working with LLMs, prompt engineering, RAG patterns, and vector search.
• A solid understanding of MLOps principles, including CI/CD for models, automated testing, and monitoring of 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, with a track record of fostering a positive, high-performing team culture.
• Excellent communication skills and the ability to translate complex technical concepts for business stakeholders.
• Strong project management skills, including resource estimation, progress tracking, and meeting deadlines in a fast-paced, multi-priority environment.
• A proactive, problem-solving mindset with the ability to operate independently and step up into a leadership vacuum when needed.
• Experience with advanced NLP techniques beyond prompt engineering, including fine-tuning and evaluation frameworks for generative models.
• Experience working in the (re)insurance industry, with an understanding of underwriting, claims, or actuarial data.
• Knowledge of responsible AI practices, including bias detection, explainability, and fairness testing.

Skills

• Python
• scikit-learn
• pandas
• PyTorch
• TensorFlow
• Databricks
• MLflow
• Spark
• Generative AI
• LLMs
• Prompt Engineering
• RAG
• Vector Search
• MLOps
• CI/CD
• Azure OpenAI
• Azure Machine Learning
• Azure AI Search
• Git
• LangChain
• Semantic Kernel

Location

• New York, NY
• Halifax, Nova Scotia

Work Type

• Hybrid

Experience Level

• Leadership
• Management

Salary/Compensations

• $175,000 - $200,000 USD (New York, NY)
• $110,000 - $130,000 CAD (Halifax, Nova Scotia)

Benefits

• Competitive target incentive compensation
• Medical plans for you and your family
• Health and wellness programs
• Retirement plans
• Tuition reimbursement
• Paid vacation

About the Company

• AXIS Capital is a trusted global provider of specialty lines insurance and reinsurance.
• We stand apart for our outstanding client service, intelligent risk taking and superior risk adjusted returns for our shareholders.
• We proudly maintain an entrepreneurial, disciplined and ethical corporate culture.
• As a member of AXIS, you join a team that is among the best in the industry.
• At AXIS, we believe that we are only as strong as our people.
• We strive to create an inclusive and welcoming culture where employees of all backgrounds and from all walks of life feel comfortable and empowered to be themselves.
• This means that we bring our whole selves to work.

Equal Opportunity

• All qualified applicants will receive consideration for employment without regard to any protected characteristic, including age, color, disability, ethnicity, gender identity, marital status, national origin, pregnancy, race, religion, sex, sexual orientation, veteran status, or any basis prohibited by the laws that govern its operations.