Data & AI
Four years of Data projects at SFR, a master in Data & AI, and one conviction: AI is only as good as the data you feed it.
A Data project manager is a translator: business needs into specifications, figures into decisions, technical constraints into a schedule.
The role, in four verbs
At SFR, Data projects involve many teams and very large volumes. The project manager holds the thread, from the first stated need to everyday use.
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Frame
Turning a business need into objectives, indicators and a clear scope.
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Coordinate
Moving business teams, data engineers and analysts forward together.
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Safeguard
Ensuring data quality, consistency and sound governance.
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Deliver
Acceptance testing, go-live, then support until adoption.
Four levels of analysis
From simple description to recommendation, each level answers a more ambitious question. AI mostly comes in at the last two.
Fictional data, for illustration only.
AI, where it really helps
No magic: AI is useful when the task is repetitive, high-volume or predictable, and when the data behind it is clean. Otherwise, a good SQL query often does better.
- Automaterepetitive tasks: sorting, data entry, reconciliations.
- Detectanomalies in a stream too large to be reviewed by hand.
- Forecasta trend to anticipate a workload, a stock level or demand.
- Summariselarge volumes of text: customer requests, meeting notes, documents.
School and work, at the same time
All of my higher education has been work-study. What is taught in class gets applied at work, and the problems met at work give meaning to the classes.
- 2020 - 2023Bachelor in Digital EngineeringESILV, work-study at Synerlink
- 2023 - 2025Master in Data & AIEFREI, work-study at SFR
- 2025 - 2027Engineering degree, LSIEFREI, work-study at SFR