Scientific Developer

16 ott - Pisa
Fondazione Start Attractor

Scope
The Scientific Developer – Data Engineer will work on digitalization processes in
the paper-making industry (with a focus on tissue, hygiene products and related
processes). The role will work 66% of the time at the industry premises and 33% of
the time at Start Attractor.
The role supports Start Attractor in: translating industrial needs (from partners and
clients) into R&D; and innovation projects; identifying and adapting scientific and
technological solutions; supporting the design, modeling, execution, and validation
of experiments, pilot trials, and prototype development.
The role with our industrial partner will be responsible for designing, developing,
maintaining, and evolving data acquisition, integration, transformation, and
orchestration pipelines from corporate and manufacturing systems. This role will
contribute to the development and evolution of the company’s Data Platform and the
data components supporting the company’s Agent Platform, working closely with
vendors and internal stakeholders to ensure data reliability, scalability, quality, and




availability for analytics, reporting, and data/AI solution use cases. In the medium
term, the successful candidate will become the internal point of reference for the
evolutionary maintenance, optimization, and governance of data platforms, including
any architectures supporting AI and agentic solutions.

Key Responsibilities
Technical & Scientific Development: analyze industrial digital challenges and needs;
identify and assess scientific and technological solutions (e-g. equipments.
processes, materials, sensors, automation) that can address those needs; support the
definition of objectives and hypotheses; experimental plans and testing protocols;
development and implementation of data-driven models; technical milestones and
KPIs. Contribute to pilot trials and experimental campaigns in collaboration with
industrial partners and research labs (design of tests, data collection, first-level
analysis); dra

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