Make sense of messy data
Taking exports, spreadsheets or systems that have grown over time and turning them into something structured, readable and ready for analysis.
Cleaning · structuring · sanity checks
Data and analytics work
What I actually do with data and analytics.
I sit in the space between raw data and real people. I clean and explore datasets, look for the patterns that matter, and then explain what I find in plain language so teams can decide what to do next.
Ways I can add value to your team
Think of these as the kinds of problems you can throw at me and trust I will move them forward, without drama or jargon.
Find the story in the numbers
Exploring patterns, asking sensible follow up questions and highlighting the few things people need to see, not the fifty charts they do not.
Exploration · insight · clarity
Bridge technical and non technical
Talking comfortably with both analysts and stakeholders, and translating between the two so nobody feels talked down to or left out.
Translation · facilitation · trust
Skills I use in this work
A mix of technical skills and human ones. Both matter if you want analysis that lands with real people.
Technical skills
- Python for data analysis (Pandas, Jupyter)
- SQL for querying and joining real world datasets
- Data cleaning, reshaping and basic validation checks
- Creating charts and visual summaries that make sense
- Comfortable with spreadsheets and dashboards
I am happiest where the work is hands on and practical, not buried in buzzwords.
Human skills
- Explaining analysis in plain, respectful language
- Listening carefully before suggesting answers
- Asking questions that surface context and edge cases
- Working with people who do not see themselves as “data people”
- Managing my time and energy around real life responsibilities
I care about people feeling informed and included, not overwhelmed or shut out.
Examples of work I am drawn to
These are types of projects I either have experience with or am actively building towards. They show how I think and where I want to contribute.
Example direction
Retention and progression analysis
Looking at who stays, who leaves and when that tends to happen. The aim is to spot patterns early enough to offer support instead of only reporting outcomes.
- Combine attendance, grades and support data
- Highlight segments most at risk of dropping off
- Produce a short, readable summary for non technical teams
Python · SQL · descriptive analytics
Example direction
Simple analytics for small teams
Working with organisations that do not have a full analytics function, helping them track a handful of useful metrics instead of drowning in reports.
- Audit the data they already collect
- Agree a small, meaningful set of measures
- Build lightweight views that can be maintained
Dashboards · reporting · prioritisation
Example direction
Translating analysis into everyday language
Taking a technical report and reworking it for the people it affects: students, parents, community partners or frontline staff.
- Identify what really needs to be understood
- Cut back jargon and unnecessary detail
- Produce short explainers and visuals
Data storytelling · facilitation
Example direction
Talks, workshops and lived experience input
Contributing to events or internal sessions where you want a grounded voice on data, access and inclusion that connects with people who do not see themselves as “techy”.
- Talks on data, routes into tech and confidence
- Panels or Q&A with students, parents or staff
- Workshops on making data feel less intimidating
Speaking · workshops · panels
Where I fit in a data and analytics team
I sit comfortably between technical detail and lived reality. Here is how that tends to look in practice.
1
The translator
I listen to stakeholders who are not technical, clarify what they really need and translate that into questions and tasks that make sense to data teammates.
2
The cleaner and explorer
I am happy to work with real world data: checking quality, tidying structures and exploring patterns before we start promising answers.
3
The narrative builder
I pull findings together into a story that people can follow, including the caveats, surprises and decisions that still need to be made.
4
The follow through
I stay involved long enough to help refine language, tweak visuals and make sure the work is actually used, not just filed away.
If you are building something and need this kind of mind
I am interested in data and analytics roles that add real value, and in projects around education and access. If that sounds like your work, I would love to hear from you.
The simplest way to reach me:
A short message with a rough idea of what you have in mind is more than enough to start.