Our story
How a research collective becomes a consulting firm.
We met at university — not in a business incubator. Our earliest collaborations were reading groups, seminar papers, and late-night arguments about methodology.
What we noticed, working through our own dissertations and early research projects, was a consistent gap: serious research questions, capable researchers, and methods that didn't quite fit — or weren't clearly documented, or hadn't been tested for reproducibility. The support that existed was either too expensive, too generic, or too far removed from the actual academic context.
AnalyticsScholar is the answer we would have wanted as students and early-career researchers. Not a service provider handing off deliverables, but doctoral-level peers who understand the epistemological stakes of getting the methods right — because they've been in the viva, the peer review, the committee meeting.
We cover quantitative and theoretical ground simultaneously — econometric modelling alongside political theory, survey design alongside sociological argumentation. That synthesis is rare and, we think, genuinely useful to researchers who need their numbers and their reasoning to hold together under scrutiny.
We apply the same standard of evidence to what we say about ourselves as we apply to your analysis.
How we work
Four principles. Not negotiable.
These aren't aspirations. They're the conditions under which we take on work.
Academic ethics, not sales targets
We turn down projects outside our expertise. We don't exaggerate credentials or inflate timelines. If we're not the right fit, we say so in the first call. Our growth is through trust, not volume.
Quantitative and theoretical, unified
Most data firms can model but can't argue. Most theory groups can argue but can't model. We hold both — econometric rigour grounded in theoretical reasoning, methods that can be defended to a sceptical examiner or reviewer.
Open source, by conviction
R, Python, Linux. No proprietary lock-in. Every analysis we produce is reproducible: annotated code, versioned datasets, documented decisions. The same transparency we expect in published science, applied to our own work.
Fixed fees, no surprises
You see the total cost before you commit. We don't bill for thinking or for scope creep we caused. Revision rounds are included. The proposal is a commitment, not an estimate.
Collaborations
What we've done and where we're going.
We only list what's real. Two tiers: completed engagements, and active collaborations in progress.
Universities
Academic collaboration with faculty and doctoral researchers. Alma mater of core team members.
Academic collaboration with faculty and doctoral researchers. Alma mater of core team members.
Foundations
Scoping conversations under way; we will name the partner once the engagement is signed and we have permission to reference it.
Early-stage discussion of a methodological review project. Listed here so the pipeline is visible, not as a claim of completed work.
Open Source
Every analysis we deliver is built on open-source infrastructure. No proprietary lock-in, no licence dependencies, no opaque black boxes.
Literate, versioned, peer-reviewable. The same documentation tools used in published reproducible science.
Work with a research collective that gets it.
Book a free 20-minute consultation. We'll discuss your project, your timeline, and whether we're the right fit.