Introduction: Solving real business problems with data

Today’s employers are looking for more than technical know-how – they want data professionals who can solve real problems, work in teams, and communicate insights clearly. That’s why the LSE Data Analytics Career Accelerator culminates in a six-week Employer Project: a live, practical business experience where learners step into the role of a data analyst and deliver solutions to real companies.

This is where technical skills meet teamwork, stakeholder engagement, and real-world delivery. Learners apply everything they’ve learned over the previous six months of the Career Accelerator to deliver value for a real company – proving to themselves (and future employers) that they’re ready for data roles.

Past learners have used the Employer Project to stand out in job interviews, build credibility with hiring managers, and demonstrate experience that many early-career analysts simply don’t have.

“[The practical experience] is probably the reason why I got through the job interview process. Having that tangible evidence… is something I could really talk about in my job interview.” 

— Jon Minto, Career Accelerator Alumnus;
Changed careers from ski instructor to data analyst

For the most recent cohort, the Employer Project meant partnering with GAEA AI, a cutting-edge company using artificial intelligence to help businesses adapt to climate-related challenges.

To give you an accurate, inside look at what it’s really like to complete the Employer Project, we interviewed GAEA AI’s founder, Graeme Scott, along with two learners – Rachel Ong and Mateusz Lisiecki – so that you can see how this experience can accelerate your growth, confidence, and career.

Get a snapshot of the brief, approach and unique outcomes of the project from Graeme himself.

“It was really exciting to work with an established company and be given the opportunity to work on a business challenge they had faced – pitching our insights to them.”

— Rachel Ong, Career Accelerator Alumna

The challenge: Optimising stock during a heatwave

In 2022, Spain experienced an extreme heatwave that resulted in a national shortage of ice, disrupting supply chains and costing businesses revenue. GAEAAI challenged learners to investigate this real-world problem using historical sales, weather, and consumer behaviour data.

The brief: Uncover the drivers behind demand spikes, pinpoint conditions that predict sales surges, and recommend strategies to optimise stock levels during critical periods.

The project kicked off with a live briefing session between learners and the Employer Partner, during which the learners could ask questions and clarify expectations – just like in a real consultancy or in-house data team.

GAEA AI’s CEO, Graeme Scott, encouraged learners to step into the mindset of a business analyst, not just a coder.

“Spend time understanding the problem. Don’t rush into coding. Define the question, the context, the stakeholders. That’s how you create insights with real business impact.”

— Graeme Scott, Founder & CEO of GAEA AI

The solution: From raw data to actionable insight

Learners worked in agile teams to tackle the brief, applying a blend of technical and business skills, including exploratory data analysis, clustering techniques, forecasting models, and insight communication.

The project challenged them to solve a complex problem from start to finish: from initial scoping and data cleaning through model development to a final presentation to the GAEA AI stakeholders.

It’s a rare opportunity to see a full data project through – not just in theory, but in execution. As Rachel said, “The Employer Project gave us the opportunity to practise our newly acquired coding skills, which enhanced our learning.”

For Rachel, this meant using Python – the focus of Course 3 – to clean messy datasets, conduct exploratory analysis, and build predictive models. The project also gave her the opportunity to dive deeper into tools she’d been introduced to: “There are so many libraries you can tap into.”

Mateusz applied techniques like K-means clustering to segment customers, and, as he explained, “built models to optimise stock forecasting, restocking and marketing strategy.” Reflecting on the challenge, he added: 

“You get to prove that you worked with a real-world business problem… the data was really messy. So you can talk about what you did to clean it, how you approached finding insights and built machine learning models.”

— Mateusz Lisiecki, Career Accelerator Alumnus

How the curriculum builds to this moment

The LSE Data Analytics Career Accelerator is designed to build fluency, problem-solving capability, and job-ready confidence through progressive, applied learning. Learners begin with foundational skills in data literacy, business problem-solving, and SQL. They then develop fluency in visualisation and data storytelling, before moving into Python programming, forecasting techniques, and machine learning. 

By the time learners reach the Employer Project, they’ve built a strong foundation and are ready to take on a real business data project.

“We needed the minimum skill level going into the project, and the Career Accelerator equipped us with a solid foundation. The project then gave us the platform to build on our existing skill set.” — Rachel 

Mentorship in action: Support, structure, and real-time feedback

Throughout the Employer Project, learners are supported by the programme team: 

• Course Facilitators provide academic support, project coaching and feedback 
• Success Managers keep learners on track with deadlines and workload
• Career Coaches help them think ahead to interviews and portfolios

This guidance is deeply practical and focused on helping learners build clarity and confidence, and strong data instincts.

“We received specific and constructive feedback from our Facilitator Andre. He told us that our visualisations were great, but we could be more specific with our insights. He asked us to highlight impactful events, be more concise in some areas, and explain our predictive model in further detail.” — Rachel 

“Andre was like a compass, making sure we didn’t waste our time… he challenged us to provide data, visualisations and analysis – only then would he give feedback.” — Mateusz 

These feedback moments become turning points, helping learners sharpen their insights, improve their narratives, and think critically about impact.

Feedback from the Employer Partner

Alongside academic guidance, learners benefit from direct engagement with the employer – a rare opportunity to receive input from senior industry leaders. In the GAEA AI project, learners presented their work at two stages and received feedback directly from CEO Graeme Scott. As Rachel reflected, “That kind of real business feedback made it feel real.”

“Graeme was very relaxed… for him there was no stupid question. He couldn’t give us answers, but he was prompting us in the right direction – which was really helpful.” — Mateusz 

“Preparing questions for our Q&A session with GAEA AI after exploring the datasets – that’s probably part of what we’ll have to do in our future roles as data analysts, and the Employer Project gave us a taste of what we might encounter.” — Rachel 

This feedback loop gives learners a taste of what it’s really like to work with stakeholders – adapting their work based on evolving needs, responding to questions, and refining their recommendations in real time.

Collaboration that mirrors the workplace

Data analysts rarely work in isolation – and neither do learners on this project. Each team organises itself like a real data team: assigning roles, scheduling check-ins, and sharing responsibility for the final outcome.

Rachel’s team used WhatsApp, Trello and Google Drive to stay organised and focused, and met multiple times a week to ensure momentum.

This collaboration isn’t just about logistics – it’s a learning opportunity in itself. Learners build soft skills like teamwork, communication, and delegation while learning from each other’s strengths.

“A huge gain from this Employer Project is the collective learning. I’ve learned quite a lot from my teammates through this process. For instance, I can refer to Python scripts they’ve created for my future projects if relevant. Working within a team – recognising and leveraging our individual strengths have contributed to the success of our project. I’ve realised what an underrated skill it is to communicate effectively within a team.” — Rachel 

Presenting with confidence: Building soft skills that matter

The project culminates in a live presentation to the employer – a moment where learners explain their methodology, walk through their recommendations, and respond to questions from industry professionals.

It’s a high-reward experience that builds communication, confidence, and composure – all critical for success in data roles.

“Combining soft skills like quick problem-solving with our technical abilities, that’s not something we’d get to do in a traditional coursework setting. This experience felt as if we were a data team solving a business challenge together.” — Rachel 

For many learners, this is a standout moment in their journey – a chance to prove to themselves and others that they can deliver under pressure.

Career impact: A real-world data project that opens doors

Learners leave the LSE Data Analytics Career Accelerator with a tangible, data portfolio project that shows employers what they’re capable of – from technical rigour to business impact. For Mateusz, who is changing careers from Senior Trials Specialist to Data Analyst, it’s given him the confidence to take the next step: “I want to go fully into data analytics. I’ve got all the tools now to find an entry role, and I know how to talk about my work with confidence.”

“This Employer Project is already live on my LinkedIn and CV. I’m thankful for it being one of my highlights especially since I have yet to accumulate other data analytics experience outside of what I’ve achieved during this Career Accelerator.” — Rachel 

“It was a massive boost of confidence that I can actually do it… from messy data to insights, collaborating with others, presenting solutions. That’s something I can speak to in interviews now.” — Mateusz 

🎯 Recent learner outcomes:

• Arthur changed careers (and countries) while on the Career Accelerator; “To get a job very quickly like that was a big achievement.” Hear his story.

• Tim launched his own AI-based marketing business after completing the programme, saying, “If I had not done this programme, I wouldn’t have a business to be pretty blunt.” Watch his interview.

• After 16 years in education, Elodie pivoted to data analytics. Since completing the programme, she’s been a Lead Data Scientist, Director of Development at a software company, and is currently a Senior Analytical Lead at the NHS and an Assitant Facilitator on the Career Accelerator. 

These success stories reflect just a handful of the transformations our learners have achieved – and offer a glimpse of the kind of impact that could be possible for you.

Why the LSE Data Analytics Career Accelerator is different

This is more than a course – it’s a Career Accelerator, built to equip learners with the career-ready data skills, experience and confidence to step into real data roles.

Here’s what makes it different:

✅ Live Employer Projects
Work with real companies, real data, and real consequences.

✅ Career-aligned curriculum
Progress through a skills ladder that mirrors the real job.

✅ End-to-end support
From instructors to industry experts, you’re guided every step of the way.

✅ Practical, portfolio-ready outcomes
Leave with projects that showcase your technical, analytical, and business capabilities.

✅ Soft skills that set you apart
Work in teams, manage stakeholders, and present like a professional.

Conclusion: From training to transformation

The Employer Project is a defining moment for our learners. It marks the shift from structured coursework to independent, real-world problem-solving, where learners apply their skills in a business context and prove their job readiness. 

For GAEA AI, it’s a valuable opportunity to engage with emerging talent and fresh thinking. For learners, it’s a powerful validation that they’re ready to step into the industry – equipped, confident, and capable of adding value from day one.

Whether you’re looking to change careers, advance in your current role, or build practical experience, the LSE Data Analytics Career Accelerator equips you with the skills, support, and real-world experience to make it happen.

Download the programme brochure to explore the full curriculum, meet past learners, and see how the Career Accelerator can help you take your next step in data.