Rob Abramowitz serves as your fractional Head of Data Science—bringing the causal rigor, GenAI architecture, and team leadership that turns a capable data org into one that actually drives decisions.
The data team is talented. The tooling is solid. The backlog is real. But decisions still happen on gut. Experiments get proposed in Q1 and don't run by Q4. Models sit in review waiting on specs that never arrive.
This isn't a headcount problem or a data quality problem. It's a leadership problem. You need someone who's built this org before—who knows how to turn a capable data team into one that actually moves the business.
"The missing piece isn't more data scientists. It's a leader who knows what to do with them."
Pricing is presented in proposals, not on websites. It invites conversation, not comparison shopping.
A strategic thought partner. When you need someone to pressure-test direction, calibrate hiring decisions, and keep your data strategy honest—without the full weekly commitment.
Weekly cadence, real org involvement. OKRs get set, experiments get run, and your exec team starts getting numbers they can actually use. Most serious buyers start and stay here.
Two days a week, fully embedded. Full org ownership—hiring, architecture, board metrics, and every decision that flows through your data function. The $350K hire, fractionally.
Interview the data team, audit the stack, present findings to leadership. The sprint fee is fixed, collected before work begins, and credited toward the engagement. It sets the tone—and it's where the real work starts.
Causal inference isn't an academic exercise here. It's the difference between data that gets cited in board decks and data that gets questioned the moment someone asks one hard question. Built at Meta, applied across industries.
GenAI architecture at the right level of abstraction. Not the fastest thing to ship—the most defensible. Knows the difference between an LLM wrapper and an actual platform, and which one your company needs right now.
Led a 14-person data science organization—not advised one from the outside. Hiring, structure, development, and the messy day-to-day work of making a team perform. The org-building is where the long-term value compounds.
Not a generalist. Not a team. One senior operator with deep experience across every layer of the data function.
Experiment design, A/B testing infrastructure, incrementality testing, and the statistical rigour to defend results in front of skeptical stakeholders.
LLM selection, RAG pipelines, evaluation frameworks, and production deployment. Built for compounding value—not technical debt six months later.
Define the metrics that actually matter, build the reporting cadence that keeps leadership informed, and eliminate the dashboards nobody reads.
Demand forecasting, churn prediction, risk modeling, and revenue attribution—grounded in statistical validity, not just a model that fits the training set.
Warehouse architecture, data modeling, pipeline design, and source-of-truth governance. The foundation that makes everything else reliable.
Segmentation, cohort analysis, LTV modeling, and the customer behavior frameworks that turn raw event data into decisions marketing and product can act on.
Process efficiency, unit economics, and the operational metrics that surface bottlenecks before they become board-level problems. Particularly strong in risk and insurance contexts.
Role scoping, team structure, interview design, and the hiring frameworks that build a data org that actually scales—not one you have to rebuild in 18 months.
Before Trutara, Rob Abramowitz built and led data science organizations at two of the most analytically demanding companies in the world.
At Meta, he operated at the intersection of experimentation, causal inference, and product decisions at scale—an environment that trains a very specific kind of rigor. At Coalition, he leads the data science function across the company's core business lines.
Trutara exists to make that experience available to the companies where it creates the most leverage: Series B and C companies with capable data teams that need a fractional data science leader — not more headcount. Think of it as a fractional CDO without the politics of a C-suite hire.
"I take on one to two engagements at a time. I want to make sure I can actually move the needle."
— Rob Abramowitz, Trutara
A direct conversation about where your data org is, what's in the way, and whether there's a fit. If there is, you'll know by the end of the call.
