At a Glance
- Tasks: Lead AI delivery projects, manage workstreams, and ensure high-quality technical execution.
- Company: Join AXIS Capital, a global leader in specialty insurance and reinsurance.
- Benefits: Inclusive culture, competitive salary, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on innovation and collaboration.
- Why this job: Be at the forefront of AI advancements and make impactful decisions.
- Qualifications: Experience in data science, AI, and strong leadership skills required.
The predicted salary is between 63000 - 77000 £ per year.
This is your opportunity to join AXIS Capital - 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 also 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.
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.
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.
How does this role contribute to our collective success?
- Enable decisions to be made with confidence, based on information not just intuition.
- Be more proactive, using information to identify new opportunities, and getting to them before our competitors.
- Realize cost savings, finding ways to make processes more efficient, enabling our people to focus on using their skills to further add business value.
This team is working to transform the way in which we do business and to enable us to effectively leverage the latest AI advancements to our competitive advantage.
The Data Science & AI Delivery Lead is a key leadership role within this 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.
What will you do in this role?
The Data Science & AI Delivery Lead acts as the right hand to the Head of Data Science & AI Delivery, taking ownership of the day-to-day execution and coordination of data science and AI delivery across strategic projects and standalone use cases.
You will play a hands-on leadership role - driving technical delivery, managing workstreams, and stepping in for the Head of when required.
This is not a purely managerial role.
You will be expected to work directly in the codebase, review and shape technical designs, and maintain deep fluency with the tools and techniques the team uses daily.
Working closely with the Head of, you will ensure projects are delivered to a high standard, on time, and with strong stakeholder engagement.
In this role you will be responsible for
- Day-to-Day
- Delivery
Leadership: 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 all 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.
- Project
Management: Own technical delivery accountability from concept through production.
Ensure solutions meet security, governance, scalability, explainability, and operational support standards.
- Technical Oversight & Contribution: Provide technical guidance on solution design, model selection, and architecture decisions, ensuring the team is taking the right approach for each use case.
- 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 RAG architectures, prompt engineering, and integration with Azure AI services (e. g., Azure Open AI, Azure AI Search).
- Ensure robust MLOps practices are followed, including model versioning, testing, deployment pipelines, and monitoring of deployed solutions for performance and drift.
- 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.
- Technical Strategy & Architecture : Own AI solution architecture and technical design standards.
Define engineering approaches for LLM applications, agentic systems, machine learning solutions, and AI platforms.
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Data Science & AI Delivery Lead employer: axiscapital
At AXIS Capital, we pride ourselves on being an exceptional employer, offering a dynamic work environment that fosters inclusivity and personal growth. As a Lloyds Reporting Actuary, you will benefit from a comprehensive benefits package, including health and wellness programs, retirement plans, and tuition reimbursement, all while working alongside some of the best professionals in the industry. Our entrepreneurial and ethical corporate culture empowers employees to bring their whole selves to work, ensuring a fulfilling and rewarding career path in the heart of the Lloyd's market.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science & AI Delivery Lead
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We think you need these skills to ace Data Science & AI Delivery Lead
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at axiscapital, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at axiscapital. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at axiscapital
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at axiscapital!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
