AI Engineer - Finance Data Pipelines & Governance in London

AI Engineer - Finance Data Pipelines & Governance in London

London Full-Time 63000 - 77000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Design and deploy AI solutions for financial services, ensuring security and governance.
  • Company: Hunter Bond, a leader in AI innovation within finance.
  • Benefits: Hybrid work model, competitive salary, and strong executive support.
  • Other info: Exciting opportunity for growth in a dynamic industry.
  • Why this job: Join a cutting-edge team shaping the future of AI in finance.
  • Qualifications: Experience in AI engineering and data pipeline design.

The predicted salary is between 63000 - 77000 £ per year.

Hunter Bond is seeking an AI Engineer to help build the future of AI in financial services from London.

This hybrid role involves turning ideas into live, governed AI systems with real budget and executive support.

You will design data pipelines, deploy AI solutions with supervision from the AI innovation team, and build agentic workflows while ensuring security and auditability across platforms.

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AI Engineer - Finance Data Pipelines & Governance in London employer: Hunter Bond

Join our leading bank, where we prioritise employee growth and a collaborative work culture. As a KYC CLM AVP in London, you'll benefit from flexible working options and the chance to lead a dynamic team in a high-growth area, driving meaningful improvements in client experience and operational efficiency. We are committed to fostering an environment that encourages innovation and professional development, making us an excellent employer for those seeking a rewarding career in banking.

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Contact Details:

Hunter Bond Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land AI Engineer - Finance Data Pipelines & Governance in London

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Hunter Bond!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AI Engineer - Finance Data Pipelines & Governance at Hunter Bond.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Hunter Bond.

Apply Directly through Our Website

When you find a suitable opening like AI Engineer - Finance Data Pipelines & Governance at Hunter Bond, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace AI Engineer - Finance Data Pipelines & Governance in London

Python
Problem-Solving Skills
SQL
Data Engineering
Communication Skills
Data Pipeline Development
API Integration

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 Hunter Bond, 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 Hunter Bond. 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 Hunter Bond

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!

Showcase Your Projects

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 Hunter Bond!

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.