Building a Data-Powered Career: Opportunity, AI & the Path from Plateau to Impact

The UK's shortage of data talent is costing the economy an estimated £57 billion each year in lost productivity. For professionals, that figure isn't abstract — it's a signal. The most future-proof careers aren't in chasing the latest tool, but in filling the widest skills gaps: turning data into decisions others can act on.

Jon Minto's career transition illustrates this shift. A year ago, he was a ski instructor. Today, as a graduate of the LSE Data Analytics Career Accelerator, he’s a data analyst at GLL, using Python to generate reports and working with complex datasets. 

His journey from ski instructor to data professional shows what’s possible for career changers who invest in structured learning that combines technical fluency, practical experience, and dedicated career coaching, the core pillars of the LSE programme.

That was the central theme of the recent online event Building a Data-Powered Career, hosted by LSE and FourthRev. The expert panel brought together:

• Nathan Shoesmith – Consultant at GC Insights, and Insights and Analysis Lead for Growth Flag, a data-intelligence platform that helps organisations identify and act on business growth opportunities across the UK economy.
• Jon Minto – an alumnus of the LSE Data Analytics Career Accelerator who pivoted from ski instructing to a full-time analyst role at GLL.
• Justine Mooney – a career coach with FourthRev, specialising in helping professionals identify transferable skills and navigate career transitions.

Together, they explored what's driving demand for data roles, how AI is reshaping the analyst's toolkit, and what skills help learners move from aspiration to impact.

If you missed it, you can watch the full event recording here

These are the top takeaways:

Why data, and why now

Demand for data skills is rising across every sector. According to the World Economic Forum, roles for data analysts and scientists are set to grow by more than 30 per cent by 2027. In the UK, the data market is projected to expand by 23 per cent through to 2033, faster than almost any other profession.

This growth isn't only about job creation. It's about the value of skills. Salaries for UK data analysts typically start at around £28,000-£43,000 for entry-level roles, with averages near £37,000 in many listings; while senior positions, especially in major organisations and high cost-locations, can command six figures.

And yet, there's a paradox: while demand is surging, organisations are still not making the most of the data they already hold.

Shoesmith explained

The opportunity isn't simply in accessing more data. It's in developing the skills to turn that data into insight, and to communicate it in a way that drives decisions.

Overcoming inertia: a career changer's perspective

For many learners, the hardest part of career change isn't acquiring skills, it's overcoming inertia. That was true for panellist Jon Minto, who shifted from ski instructing into a full-time data analyst role.

He had begun with free resources, YouTube tutorials, online short courses, even Google Analytics certifications, and tested his skills on small projects. But when it came to breaking into the industry, self-study wasn't enough.

Writing later about his journey on LinkedIn, Jon reflected that what finally made the difference was the structure, community and coaching he received on the LSE Career Accelerator: 

• Structured learning gave him momentum and a portfolio of projects to show employers
• Career coaching helped him tell his story and map transferable skills onto new data capabilities
• A peer community turned a lonely process into a shared journey, keeping motivation high

Within four months of graduating, Jon landed his first analyst role. A year later, he emphasised that perseverance, support, and community were just as important as technical skills in making the leap.

For career changers, the challenge isn't just technical. It's about breaking inertia with structured support and proof of ability, moving from curiosity to confidence.

AI as co-pilot, not competitor

A recurring question from prospective Career Accelerator learners is whether AI could make analyst roles redundant. It's a concern echoed in headlines, but the reality is more nuanced. According to the World Economic Forum's Future of Jobs Report 2023, AI is expected to displace 85 million jobs globally by 2025 — but create 97 million new ones in the same period, many of them in data-related fields.

The event panel was clear: AI automates tasks, not careers.

For Minto, AI has already become part of his workflow:

The winners won't be those who ignore AI, nor those who rely on it blindly. They'll be the analysts who know when to let automation speed up routine tasks, and when to step in with human judgement, context, and influence. 

The skills employers value most

If AI is shifting the baseline, what will set analysts apart? Employers are signalling a clear mix: technical fluency plus human skills.

Core technical skills for the coming year include:

• Python for analysis and automation
• SQL for querying and structuring large datasets
• Tableau (or Power BI) for visualising insights
• AI literacy to speed up workflows and sharpen insights

Human skills that differentiate:

• Curiosity — asking better questions of data
• Communication — translating complexity into clarity
• Storytelling — turning findings into actionable recommendations
• Data visualisation — making insights easy to grasp

Shoesmith emphasised: 

Minto's experience backs this up. Within weeks of starting his role, he was able to take ownership of a Python-driven reporting task, something his manager hadn't expected a new hire to be able to handle:

Technical skills may open the door, but communication and application keep you in the room. Analysts who can bridge the gap between models and meaning will stand out in competitive hiring markets. 

Beyond a first job: careers, not just roles

Career coach Mooney warned that one of the biggest mistakes aspiring data analysts make is focusing only on landing that first analyst role. The real challenge — and opportunity — lies in building a career that compounds over time.

As she put it: "This isn't a job accelerator, it's a Career Accelerator. So it's not just that first role"

The panel stressed that transferable strengths — from teaching, operations or even sport — can accelerate your impact once you enter a data role. Curiosity, resilience, and comfort with ambiguity are qualities employers notice quickly.

Minto's own journey underscores this. His ski instructing background might not look "data-driven" on paper, but the discipline of planning, performance analysis, and clear communication translated into the professional behaviours valued in his analyst role.

The most successful data career changers aren't those chasing the perfect first job title. They're those who invest in skills, support and networks that continue to pay off long after the first step.

The path ahead

Across the event panel’s discussion, a single theme emerged: building a data-powered career isn't just about tools or titles. It's about judgement, knowing what questions to ask, what evidence to trust, and how to communicate insights with clarity.

As the panel showed, the real differentiator is not just knowing the tools, but proving how you apply them in context, and how you continue to grow beyond the first role.

Interested in exploring these themes further? Download the programme brochure to see how the LSE Data Analytics Career Accelerator could help you build both technical fluency and career confidence.