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

Apply Now

IT Project Manager

Dublin
7 months ago
Applications closed

Related Jobs

View all jobs

Project Manager - Data Analyst - SC Cleared - Hybrid

Clinical Data Science Unit Technical Project Manager

Google Data Analyst

Data Analyst - Integrations

Data Engineer – use your expertise to integrate, analyse and visualise data from our Defence cu[...]

Data Science Graduate

IT Project Manager – Data & Analytics Projects

We are looking for an experienced IT Project Manager to lead the end-to-end delivery of complex Data & Analytics projects. This hybrid role, based in Dublin, requires 2–3 days on-site per week.

Key Responsibilities:

  • Manage full project lifecycle across data-focused and other technical initiatives.

  • Develop and maintain detailed project plans, budgets, and resource schedules.

  • Lead testing, release management, and transition to operational service.

  • Operate within a PMO framework, ensuring compliance with governance standards.

  • Provide regular updates to senior stakeholders including the CIO and Head of PMO.

    Required Skillset:

  • Proven experience delivering at least three high-profile Data & Analytics projects in complex IT environments.

  • Full project lifecycle management, from planning through to delivery and handover.

  • Strong stakeholder, vendor, and team management capabilities.

  • Familiarity with Microsoft Azure, Microsoft Fabric, or similar cloud data platforms is highly beneficial.

    Desired Certifications:

  • PRINCE2, PMP, or equivalent

  • ITIL Certification

  • Agile Certification (e.g., CSM or PSM)

  • Microsoft Azure Data Engineer Certification (DP-203 or equivalent)

    If you are a certified, delivery-focused PM with a passion for data and transformation, please reach out for more information

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

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

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.