About Lauren · About EmpaCore

Data, care and a life shaped by learning.

EmpaCore is the work of Lauren Hargreaves, a data analyst from Liverpool who came back to education later in life. It brings together technical skills, lived experience and a lot of kitchen table graft to support people who are clever, stretched and often underestimated.

Based in Liverpool, UK
Focus Data and analytics work that adds real value
Thread Education, access, inclusion, story

What EmpaCore means in practice

The name blends empathy and core. It is a reminder that behind every metric is someone juggling childcare, rent, health, shifts or all of the above.

People at the centre of the data

Analysis should help real people make real choices. I want teams to see where support is landing, who is missing, and what might happen if nothing changes.

Clear language, honest limits

Jargon is easy. Clarity is harder. I aim for explanations that land with busy humans, including where the data is thin or cannot answer the question.

Tools that fit real lives

I care about approaches that work at a kitchen table, on a shared laptop or in a stretched college department, not just in ideal settings.

The longer story behind EmpaCore

CVs often tidy up the edges. The reality is more layered. This is the part that explains why I care about confidence, access and making tech feel possible.

I became a mum young and learned to carry a lot quietly. Money, time and energy were always being negotiated. Tech careers felt like something other people did in other cities, with more certainty and more safety nets.

Years later, I went to a college open day and joined the shortest queue. It turned out to be a Level 2 IT course. I liked the problem solving and the feeling that if I worked hard I could build something that actually worked. That decision led to Level 3, then HNC, then HND and eventually a First Class degree in Computer Science.

That progress was never neat. There were pauses, doubts and moments where it would have been easier to stop. Studying while parenting meant learning to squeeze work into late nights and early mornings, often with a lot of second guessing in the background.

Through all of that, I noticed the same pattern. People are capable, curious and determined, but they often lack time, guidance or confidence. EmpaCore grew from that observation. It is my way of bringing technical skills back to the communities and conversations that shaped me.

How I moved into data and analytics

My route is a series of small, stubborn steps rather than a straight shot. This is how it unfolded.

College open day

Chose the shortest queue and landed in a Level 2 IT class. Discovered I actually enjoyed code and logic, even after years away from formal study.

Starting again, from the basics

Building foundations

Worked through Level 3, HNC and HND. Learned to handle real assignments, group work, deadlines and a lot of self doubt alongside parenting.

Step by step progress

Computer Science degree

Completed a Computer Science degree and graduated with First Class honours. Found my interest narrowing in on data, insight and how to explain it well.

Data as the through line

EmpaCore taking shape

Started sharing how I use data and AI in everyday life, especially in education and learning. EmpaCore became the name and the container for that work.

From personal story to shared work

How I like to work with data and people

The tools evolve but the principles stay steady. These are the things I bring into every project, whether it is a small analysis or a longer engagement.

Context first, tools second

I start with the problem and who is affected. I care about the story behind the numbers and what will count as a useful answer for the people involved.

Clear, grounded communication

I avoid jargon unless it genuinely helps. I prefer charts, language and formats that people can challenge, share and act on with confidence.

Care for access and inclusion

I pay attention to who might be missing from the dataset or the conversation and what that means for the conclusions we draw.

Realistic use of AI

I see AI as an extra pair of hands and eyes, not a magic answer. I am interested in how it can support learning and analysis without over claiming.

If this sounds like someone you could work with

I am open to data and analytics roles that add real value, project work around access and learning, and collaborations with organisations who care about people as much as performance.

You are very welcome to reach out:

A quick, honest chat is often the best way to see if there is a good fit.