Fractional data science lead for manufacturing
Digital transformation projects are underway, but there's no senior person to own the data side. Work is split across vendors and priorities shift often.
▶ The solution
If you have no data team, or are just building one, I act as a part-time senior data lead: setting priorities, running projects and helping you build the team when it's needed.
▶ Use case
As a fractional data science lead I set priorities, review vendor projects technically and support hiring the first data team.
▶ Data you need
To start, a list of current systems, running projects and management's priorities is enough.
The industry's data landscape
In manufacturing, data usually lives in the ERP (orders, stock, purchasing), in production tracking (downtime, scrap, shifts) and in quality records. These systems rarely talk to each other; even the same product can carry different codes in each. So the first job is often to bring them together in one table.
A fractional data science lead takes on the senior data leadership role in your company on set days of the week. They own the data and AI roadmap, prioritize and run projects, and guide the existing team if there is one.
The math behind it
Priority score (RICE) = Reach × Impact × Confidence / Effort
- Reach: people or transactions affected per period
- Impact: benefit to each (scaled score)
- Confidence: how sure you are of the estimates (%)
- Effort: work required (person-months)
How I work
- First month
Situation and priorities.
Data, systems, teams and ongoing projects are reviewed. The work that contributes most to business results is identified and a written roadmap comes out.
- Following months
Running the projects.
Prioritized projects get delivered, and where needed I do part of the work myself. Management gets regular, readable progress reports.
- When needed
Team and hiring.
If a team is to be built, role definitions are written, candidates are assessed technically, and new joiners are supported as they start.
- At the end
Handover.
The goal is not to stay forever. When a team or a full-time lead is ready, responsibility is handed over with the roadmap, processes and documentation.
▶ Questions and answers
Fractional data science lead for manufacturing — what data do you need?
To start, a list of current systems, running projects and management's priorities is enough.
When is this the wrong choice?
You want to finish one project. A fixed-scope pilot or project is the better frame. A monthly leadership role isn't needed. You already have a strong data lead. A second lead creates confusion. If you need support on a specific topic, working per project is better.
How does this work start?
With a short intro call. I listen to what you need and tell you plainly whether your data is enough for the job and what the first step should be. I reply to every message within 24 hours.
▶ Concepts
Linked to Wikipedia and Wikidata.
▶ Sources
- [1]Intercom, RICE: Simple prioritization for product managers, 2016. www.intercom.com/blog/rice-simple-prioritization-for-product-managers/
- [2]Wikipedia, Chief data officer, 2026-10. en.wikipedia.org/wiki/Chief_data_officer
▶ Intro call
Let's talk about your situation.
In a 30-minute call I listen to what you need and tell you plainly how I can help.
Book an intro call▶ In other industries