Verified Job
IT / Software / Data Analyst
Graduate Data Analyst
IT / Software / Data Analyst
#49703
Remote / WFH
Native
Job Description
£33,000 IC1 Insights Mae Anderson
Location: London (office-based, ~4 days per week)
Build Something That Matters
native has been building for ten years and still runs like a startup: small, fast, and unsentimental about how things get done. We run a managed marketplace that connects students, Students' Unions, universities and advertisers. We increase student engagement, we help Students' Unions fund themselves properly, and we give advertisers a measurable route to a student audience. The closer those three line up, the better the business works.
Insights is where that audience becomes legible. We turn survey data, behavioural signals and platform data into the research brand partners buy and the segmentation that shapes how they reach students. We're looking for graduates who want real work immediately, learn at speed, and grow into something bigger.
What we're looking for
We value clarity of thought, good judgement when the pressure's on, and the instinct to build structure where there isn't any.
You might be right for this if:
You think from first principles and build answers from the ground up
You can decide when there's no map, and you build structure where there isn't any
You care that the work is right, so you check it
You have range. You've done real things that demanded resilience, judgement or initiative
We're open to a wide range of degrees. Intellectual sharpness and structured thinking turn up most often in economics, statistics, the sciences, social sciences, geography, maths or computer science, though strong thinkers come from plenty of other backgrounds too. If your path is less typical, tell us how it shaped the way you think and why that stands up.
What you'll be working on
This is a broad data analyst role. The work runs from the survey and platform data we collect to the reports and analysis that go in front of partners. The mix of data analysis, survey research and visualisation shifts week to week, and we expect you to move across all of it.
You'll be hands-on with:
The analysis behind our insights, from raw data to the charts and the written finding
Survey data from Campus Voice and our commissioned studies: cleaning it, weighting it, and reading what it actually says
SQL against our BigQuery platform, pulling and shaping the datasets the team runs on
Clear visualisations for our reports, and the charts and numbers that feed our commercial pitches, from local advertisers to national brands
Crosstabbing survey and behavioural data against our student personas and segments, so a commercial pitch can show an advertiser exactly who it's reaching and how the segments differ
Keeping survey instruments, notebooks and documentation in a state where the research runs again next quarter without an archaeology dig
Working with the engineering team to sharpen the datasets and pipelines the insights work leans on, and flagging what's slow or fragile because you're the one using it
How the work gets done
We build with agentic coding tools, and you will too. It's how an analyst here turns a question into a checked answer in an afternoon, work that used to take a week.
Used well, these tools ask more of you. The model is fast and often wrong in ways that look right: a query that runs clean and returns the wrong number, a chart that's plausible and misleading. So the job is judgement. You frame the question and decide what a good answer looks like before you let the model near it. You treat what it gives you as a first draft and check it, and you catch the analysis that's confident and quietly wrong. You own the output, including the parts the model wrote, and you can defend it with the tool closed.
If that sounds like more work than just doing a small analysis by hand, sometimes it is. That's the trade for everything larger that now fits in a day. The analysts who get the most out of these tools are the ones who were already rigorous. That rigour is what we're hiring for.
Required skills
You've excelled at something, and we're not precious about the form: first-class honours, a Dean's List, a research result, a project you couldn't leave alone. We're reading for rigour and clarity of thought
You can reason statistically: you understand sample bias and weighting, what a significance test is actually telling you, and how to interpret a regression. From coursework, a competition, or a real project
You're commercially curious: genuinely interested in how brands reach audiences and what makes a finding worth paying for
Location: London (office-based, ~4 days per week)
Build Something That Matters
native has been building for ten years and still runs like a startup: small, fast, and unsentimental about how things get done. We run a managed marketplace that connects students, Students' Unions, universities and advertisers. We increase student engagement, we help Students' Unions fund themselves properly, and we give advertisers a measurable route to a student audience. The closer those three line up, the better the business works.
Insights is where that audience becomes legible. We turn survey data, behavioural signals and platform data into the research brand partners buy and the segmentation that shapes how they reach students. We're looking for graduates who want real work immediately, learn at speed, and grow into something bigger.
What we're looking for
We value clarity of thought, good judgement when the pressure's on, and the instinct to build structure where there isn't any.
You might be right for this if:
You think from first principles and build answers from the ground up
You can decide when there's no map, and you build structure where there isn't any
You care that the work is right, so you check it
You have range. You've done real things that demanded resilience, judgement or initiative
We're open to a wide range of degrees. Intellectual sharpness and structured thinking turn up most often in economics, statistics, the sciences, social sciences, geography, maths or computer science, though strong thinkers come from plenty of other backgrounds too. If your path is less typical, tell us how it shaped the way you think and why that stands up.
What you'll be working on
This is a broad data analyst role. The work runs from the survey and platform data we collect to the reports and analysis that go in front of partners. The mix of data analysis, survey research and visualisation shifts week to week, and we expect you to move across all of it.
You'll be hands-on with:
The analysis behind our insights, from raw data to the charts and the written finding
Survey data from Campus Voice and our commissioned studies: cleaning it, weighting it, and reading what it actually says
SQL against our BigQuery platform, pulling and shaping the datasets the team runs on
Clear visualisations for our reports, and the charts and numbers that feed our commercial pitches, from local advertisers to national brands
Crosstabbing survey and behavioural data against our student personas and segments, so a commercial pitch can show an advertiser exactly who it's reaching and how the segments differ
Keeping survey instruments, notebooks and documentation in a state where the research runs again next quarter without an archaeology dig
Working with the engineering team to sharpen the datasets and pipelines the insights work leans on, and flagging what's slow or fragile because you're the one using it
How the work gets done
We build with agentic coding tools, and you will too. It's how an analyst here turns a question into a checked answer in an afternoon, work that used to take a week.
Used well, these tools ask more of you. The model is fast and often wrong in ways that look right: a query that runs clean and returns the wrong number, a chart that's plausible and misleading. So the job is judgement. You frame the question and decide what a good answer looks like before you let the model near it. You treat what it gives you as a first draft and check it, and you catch the analysis that's confident and quietly wrong. You own the output, including the parts the model wrote, and you can defend it with the tool closed.
If that sounds like more work than just doing a small analysis by hand, sometimes it is. That's the trade for everything larger that now fits in a day. The analysts who get the most out of these tools are the ones who were already rigorous. That rigour is what we're hiring for.
Required skills
You've excelled at something, and we're not precious about the form: first-class honours, a Dean's List, a research result, a project you couldn't leave alone. We're reading for rigour and clarity of thought
You can reason statistically: you understand sample bias and weighting, what a significance test is actually telling you, and how to interpret a regression. From coursework, a competition, or a real project
You're commercially curious: genuinely interested in how brands reach audiences and what makes a finding worth paying for
