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

Apply Now

Team Leader

Liverpool
6 months ago
Applications closed

Related Jobs

View all jobs

Group ICT Data Analyst

Data Engineering Lead – Elite HFT Firm - Trading Systems - WFH - London - Up to £600k TC

Lead Data Architect

Workforce Data Analyst

Principal Data Architect

Head of Data Analytics & Insights

As a Team Leader, you will bring a strong background in recruitment, with preferred experience in oil and gas, hydrogen, nuclear, or carbon capture sectors. You possess an entrepreneurial spirit and a start-up mentality, essential for innovating and driving growth in our dynamic environment. Your proven ability to build and lead effective teams, combined with a knack for leveraging data to optimize recruitment processes, makes you ideal for this role. A plus would be excellent communication skills and problem-solving prowess, enabling you to foster a collaborative and high-energy team culture that aligns with continuous improvement and strategic goals.

Responsibilities

Team Empowerment and Growth

  • Cultivate a data-driven, growth-focused team culture that thrives on collaboration, high energy, and performance.

  • Coach team members, empowering them to reach their full potential and drive recruitment metrics.

  • Keep morale high and foster an environment where people love to come to work.

    Performance and Development

  • Set ambitious, data-backed goals and empower the team to exceed them.

  • Utilize metrics to identify performance trends and guide team improvement.

  • Conduct regular performance reviews with an emphasis on growth, learning, and celebration of achievements.

    Data-Driven Recruitment Strategy

  • Leverage data analytics to enhance recruitment efficiency, spot trends, and optimize the hiring pipeline.

  • Experiment with new recruitment hacks to scale up candidate engagement and improve conversion rates.

  • Identify and pursue business growth opportunities by analyzing market and customer data.

    Fun and Collaborative Culture

  • Foster an environment that values fun, team bonding, and creative thinking.

  • Recognize individual strengths and create tailored career growth opportunities.

  • Encourage open communication, making it easy for team members to share ideas and feedback.

    Business Growth and Strategy

  • Drive recruitment success through actionable, data-driven insights.

  • Offer strategic input to address recruitment challenges, setting a roadmap for sustainable growth.

  • Coordinate training sessions to maximize system use, performance, and team efficiency.

    Client and Account Engagement

  • Develop strong client relationships, ensuring expectations are exceeded through proactive communication and exceptional service

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.