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

Apply Now

Head of People Operations

Trafford Park
6 months ago
Applications closed

Related Jobs

View all jobs

Senior Business Intelligence Analyst (6 month fixed term)

Head of Data Science Technology (Product, Engineering, Design) · London ·

Head of Data Analytics & Insights

Head of Data Analytics & Insights

Head of Data Science

Senior Director, Head of Business Intelligence

Head of People Operations

Location: Manchester

Contract Type: Full-time, Permanent

Hours: 37.5 per week

Salary: £55,000 – £65,000, dependent on experience 

We are brave, bold and inclusive – this is UA92.

At UA92, we do things differently. We are on a mission to develop the next generation of talent who are ready to make an impact in the world. Now, we’re looking for a highly experienced and strategic Head of People Operations to join our People and lead the delivery of first-class HR operations across the entire employee lifecycle.

The Role

As Head of People Operations, you’ll be responsible for leading a dedicated team across HR Business Partnering, Payroll, Recruitment, and Administration. Reporting to the Chief of People and Place, you will ensure legal compliance, operational excellence, and alignment with our strategic goals.

You’ll champion efficient, compliant, and people-focused processes, supporting everything from onboarding to employee relations, while driving change and continuous improvement across HR systems, policy, and performance culture.

What You’ll Do:

Lead, develop, and inspire the People Operations team, ensuring best-in-class service delivery.
Oversee policy development and ensure compliance with employment legislation.
Provide strategic support on complex employee relations matters and organisational change.
Manage payroll operations and reward processes to ensure accuracy and compliance.
Use people data and systems to deliver insight and guide strategic decision-making.
Foster a culture of collaboration, inclusion, innovation, and high performance.

What We’re Looking For:

CIPD Level 7 or equivalent experience.
Significant experience in a senior HR role with a strong understanding of employment law and payroll operations.
Proven ability to manage complex employee relations cases with legal risk awareness.
Strong leadership skills and experience managing a multi-disciplinary HR team.
A high degree of integrity, with exceptional interpersonal, organisational, and analytical skills.
Familiarity with HR systems and data analytics, with a passion for innovation and improvement.
A values-led, collaborative approach with a genuine commitment to staff experience and wellbeing.

When you click apply you will be taken to our careers page to complete your application

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.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

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.