Head of AI Technology - AI Innovation Team - Head of Data Science & Data Software Engineering

JR United Kingdom
London
9 months ago
Applications closed

Related Jobs

View all jobs

Head of Artificial Intelligence Impact

Principal Data Scientist & Machine Learning Researcher

Head of DevOps and DataOps

Head of Machine Learning (Recommendations, AI Stylist & Search)

Vice President, Head of Discovery Data Science

Lead Machine Learning Engineer, AI

Social network you want to login/join with:

Head of AI Technology - AI Innovation Team - Head of Data Science & Data Software Engineering, London

Client:

Aventis Solutions

Location:

London, United Kingdom

Job Category:

Other

EU work permit required:

Yes

Job Views:

4

Posted:

28.04.2025

Expiry Date:

12.06.2025

Job Description:

Aventis Solutions has partnered with a fast-growing Anglo-American tech team seeking a Head of AI, Data Science & Data Engineering (Software Engineering) to architect, build, and deliver an innovative AI strategy and drive transformative AI initiatives company-wide. This is your chance to be at the forefront of innovation, leveraging cutting-edge technology to create solutions that matter.

Salary: £150,000-175,000 + 25% bonus + 18% pension contribution + private healthcare allowance + strong benefits package

Location: Remote-based + London HQ + New York tech team (very flexible on travel)

Future Outlook: There will be potential for vertical and horizontal progression in this role as the firm expands. Potential to be a fully-fledged CAIO as you prove the capability.

  • Data/AI Pedigree: Proven experience in senior leadership roles focused on data, artificial intelligence, or software engineering / information technology.
  • Tech-savvy: Proficiency in modern data technologies (e.g., cloud platforms, big data ecosystems, AI frameworks such as Databricks, Snowflake, BigQuery, Microsoft Fabric, or similar).
  • All-rounder: Strong knowledge of key CDO/CAIO areas such as AI/Data Governance/Quality/Management, Data Engineering, Data Science, Data Operations, Data Architecture.
  • Commercial: Exceptional strategic thinking with the ability to align AI initiatives to business goals. Always looking for synergies with other departments' strategies.
  • Leader: Strong leadership skills with a track record of mentoring multidisciplinary teams, scaling teams, and working with other leaders, including finance, HR, and marketing.
  • AI Market Knowledge: Understanding of ethical AI principles, data privacy regulations, and emerging AI trends. (We can always hire someone for this, though!).
  • Financial Services: Knowledge or experience working for or with banks, insurers, asset managers, or similar.
  • Innovative: A genuine passion for innovation, combined with pragmatism to deliver high-impact solutions. Experience with modern tech like Cursor AI, LLMs (ChatGPT, Groq, or similar), and Azure ML is a bonus.
  • Communication: Fluent in written and spoken English.

Role Overview:

Head of Artificial Intelligence Technology Team: This team will be expanding gradually, and this role will be crucial to leading the development and management of truly innovative data science / AI technology capabilities. This forms part of a new AI Innovation Team, akin to a research and development lab initiative, so we seek individuals who can drive this forward. Heavy financial investment has already been made into the R&D lab for tech innovation, providing access to advanced tools and resources to push AI and digital innovation boundaries.

Interested?Please submit your CV via LinkedIn or message Billy Hall for further information.

Aventis Solutions is acting on behalf of our partner.

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.