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

Apply Now

Senior Recruitment Consultant - AI & Data Science - Manchester

Ruth Moran
Greater Manchester
3 months ago
Applications closed

Related Jobs

View all jobs

Senior Quantitative Recruitment Consultant

Interim Finance & MIS Director | Strategy & Data Governance

Senior Business Intelligence Developer

Senior Data Engineering Consultant - £60,000 - Hybrid

Senior Consultant Data Scientist

Data Scientist Senior Consultant - Belfast

Senior Recruitment Consultant - AI & Data Science

Location: Manchester City Centre


Salary: £25,000 - £40,000 + high OTE (uncapped commission)


Are you passionate about the transformative power of AI and data science? Our client is Manchester's leading specialist recruitment agency in artificial intelligence and data sectors who are now expanding their presence across Europe and the USA.


About Us


They're a mid sized boutique recruitment consultancy dedicated exclusively to the AI and data science sectors. Their team of specialist recruiters are on a mission to build the most elite and high-performing research and engineering teams in the industry. Their focus on cutting-edge areas including:

Quantum Computing


Reinforcement Learning
MLOps
Recommender Systems
Large Language Models
Computer Vision
Neural Networks

Their client portfolio includes innovative startups, scale-ups, and Fortune 500 companies at the forefront of technological advancement. 


The Role


As a Senior Recruitment Consultant, you'll be responsible for:

Building and maintaining relationships with key clients in the AI and data science sectors


Identifying and approaching passive candidates through multiple channels
Managing the full recruitment lifecycle from job qualification to placement
Staying current with AI and data science industry trends and developments
Contributing to our company's growth strategy in European and US markets
Collaborating with our specialist team to deliver complex technical hiring projects
Understanding and evaluating technical requirements for AI research and engineering roles

What We're Looking For

1+ years of recruitment experience (tech recruitment preferred but not essential)


Strong business development and networking abilities
Excellent communication and negotiation skills
Self-motivated with a proven track record of achieving targets
Genuine interest in artificial intelligence and emerging technologies
Ability to understand and discuss technical concepts with clients and candidates
Second language skills beneficial but not essential (German, French, or Spanish)

Benefits

Comprehensive training in AI and data science recruitment


International travel opportunities to client sites and tech conferences
Regular team socials and wellness initiatives
Private healthcare and dental cover
25 days holiday + bank holidays
Flexible working arrangements
Career progression opportunities
Modern office in Manchester City Centre

Career Development


They invest heavily in their consultants' personal growth, offering:

Structured career path to Senior/Principal Consultant and Team Lead roles


External training and certification opportunities
Mentoring from industry veterans
Access to global tech conferences and events
Technical training to understand AI and ML fundamentals
Regular knowledge sharing sessions with AI practitioners

To embark on the next leg of your exciting career in this cutting edge space, contact Barrie Dewhirst at Ruth Moran Consulting. or email

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

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

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

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.