I’m Shannon Ross-Sheehy, PhD — cognitive scientist, professor, and data consultant. I help teams turn noisy, real-world data into answers you can act on, pairing clean analysis with visuals that make the point fast.
I work with nonprofits, researchers, and mission-driven teams to organize messy datasets, create reproducable analyses, and build clear visuals so you can see what matters. I keep the process practical and collaborative — no jargon, just useful insight.
I’m also an Associate Professor of Psychology & Neuroscience. Teaching is in my bones — I bring that same clarity and structure to client work: set the question, shape the data, choose the right methods, and tell the story plainly.
I offer flexible structures depending on your needs — from one-time deep dives to ongoing monthly support.
Focused engagements for specific questions, analyses, or deliverables. Great for projects with clear scope and defined outcomes.
A structured first look at your data; surface problems, highlight quick wins, and suggest next steps.
Data analysis and visualization designed to reveal meaningful patterns and support confident, evidence-based choices.
Partnering with you from the research question forward — aligning methods, measures, and analysis to generate data that truly answer what you need to know.
*Rush projects from $325/hr • Nonprofit discounts available.
Consistent support for teams that want ongoing analysis, rapid feedback, and a dedicated partner on call. Preferred rates.
Up to 10 hrs/mo · Best for light, ongoing analytic support. Quick answers to questions, targeted analyses and visualizations, and regular check-ins.
Up to 20 hrs/mo · A balanced option for teams who have specific project needs. Routine analyses, monthly reporting, and regular check-ins to keep decisions on track.
Up to 40 hrs/mo · Comprehensive support across multiple projects. Deep-dive analyses, visualizations, reporting, and strategy sessions. Ideal for organizations needing dedicated support.
*Retainers billed monthly.
Short explainers showing how findings from our lab and others can help us understand how people best perceive information — and how to design analyses and visuals that maximize clarity and impact.
We can only process a narrow slice of what’s in front of us, while everything outside that focus fades into the background. In data visualization, this means what you emphasize becomes the story your audience remembers. Well-chosen visuals focus attention, while clutter muddies the message and overwhelms attention. Effective design is about steering focus toward the points that matter most.
People can only juggle a few chunks of information at once — usually around 3–5 meaningful units. This well-known bottleneck has big implications for data work. If you present too many ideas at once, important details can be lost. Good analysis isn’t just about accuracy; it’s about structuring information so the brain can hold onto it long enough to compare, reason, and decide.
FocusIQ isn’t just about answers — it’s about asking the right questions so your data works harder for you.
# Fun fact
if is_murky(data):
insights = FocusIQ(data)
print("From murky to meaningful → FocusIQ")Whether you’re leading a classroom, a firm, a lab, or a company — or just curious what your data can teach you — let’s talk.