Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Gen AI Specialist

London
6 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Azure AI Data Engineer

Data Engineer

Data Engineer

Gen AI Specialist
Location: Canary Wharf, London (3 days onsite)
Contract Length: 10 months
Daily Rate: £800 - £850 (inside IR35 via umbrella)

Are you a seasoned Data Scientist with a passion for Generative AI? Our client is seeking a Gen AI Specialist to join their dynamic Technology team in Canary Wharf. This role offers an exciting opportunity to work on innovative solutions that address complex financial data challenges, particularly in credit risk management.

Key Responsibilities:

Lead the development and coordination of analytical plans, ensuring alignment with various teams.
Manage deliverables in an agile environment while maintaining clear and effective communication with stakeholders.
Present analytical findings, updates, and challenges to diverse audiences including business units, technology management, and risk review teams.
Execute data modelling and cleaning processes utilising both internal and external data sources.
Build predictive and prescriptive models through data manipulation and cleaning.
Design, manage, and deploy analytical solutions leveraging Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs) into production systems following the technology SDLC process.
Implement features throughout the ML lifecycle-Development, Testing, Training, Production, and Monitoring-to ensure the scalability and reliability of solutions.Qualifications:

PhD or master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
Minimum of 5 years of industry experience as a data scientist, with a focus on ML modelling, Ranking, Recommendations, or Personalization systems.
Proven track record of designing and developing scalable and reliable machine learning systems.
Strong expertise in ML/DL/LLM algorithms, model architectures, and training techniques.
Proficiency in programming languages such as Python, SQL, Spark, PySpark, TensorFlow, or equivalent analytical/model-building tools.
Familiarity with tools and technologies related to LLMs.
Ability to work independently while also thriving in a collaborative team environment.
Experience with GenAI/LLMs projects.
Familiarity with distributed data/computing tools (e.g., Hadoop, Hive, Spark, MySQL).
Background in financial services, including banking or risk management.
Knowledge of capital markets and financial instruments, along with modelling expertise.

If you are a forward-thinking individual with an adaptive mindset ready to tackle complex business problems, we want to hear from you! Join our client's innovative team and contribute to the future of financial data analysis.

To Apply: Please submit your CV and a cover letter detailing your relevant experience and interest in the role.

Our client is an equal opportunity employer and welcomes applicants from diverse backgrounds.

Adecco is a disability-confident employer. It is important to us that we run an inclusive and accessible recruitment process to support candidates of all backgrounds and all abilities to apply. Adecco is committed to building a supportive environment for you to explore the next steps in your career. If you require reasonable adjustments at any stage, please let us know and we will be happy to support you

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.

Data Engineering Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data engineering hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise reliable pipelines, modern lakehouse/streaming stacks, data contracts & governance, observability, performance/cost discipline & measurable business outcomes. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for platform‑oriented DEs, analytics engineers, streaming specialists, data reliability engineers, DEs supporting AI/ML platforms & data product managers. Who this is for: Data engineers, analytics engineers, streaming engineers, data reliability/SRE, data platform engineers, data product owners, ML/feature‑store engineers & SQL/ELT specialists targeting roles in the UK.

Why Data Engineering Careers in the UK Are Becoming More Multidisciplinary

For many years, data engineering in the UK meant designing pipelines, moving data between systems, and ensuring analysts had what they needed. Today, the field is expanding. With cloud platforms, machine learning, real-time analytics and the explosion of sensitive personal data, employers expect data engineers to do much more. Modern data engineering is no longer just about code and storage. It requires legal awareness, ethical judgement, psychological insight, linguistic clarity and human-centred design. These disciplines shape how data is collected, processed, explained and trusted. In this article, we’ll explore why data engineering careers in the UK are becoming more multidisciplinary, how law, ethics, psychology, linguistics & design now influence job descriptions, and what job-seekers & employers must do to thrive.

Data Engineering Team Structures Explained: Who Does What in a Modern Data Engineering Department

Data has become the lifeblood of modern organisations. Every sector in the UK—finance, healthcare, retail, government, technology—is increasingly relying on insights derived from data to drive decisions, deliver products, and improve operations. But raw data on its own isn’t enough. To make data useful, reliable, secure, and scalable, companies must build strong data engineering teams. If you’re recruiting for data engineering or seeking a role, understanding the structure of such a team and who does what is essential. This article breaks down the typical roles in a modern data engineering department, how they collaborate, required skills and qualifications, expected UK salaries, common challenges, and advice on structuring and growing a data engineering team.