Data Scientist Lead

19 set - Firenze
Team.Blue

Overview
In this role, you will lead a small data science team while remaining hands-on, using data-driven insights to shape business decisions.
You'll own complex projects end-to-end, aligning data work with strategic objectives and cross-functional needs.
You'll translate technical findings into business value through ML, forecasting, and analysis, driving measurable outcomes.
This hybrid role combines leadership with active coding to maintain high technical standards and impact.
Responsabilità
Lead and develop a two-person data science team, setting objectives and guiding growth
Stay hands-on by delivering the most complex projects and performing code reviews
Plan and prioritise the team backlog, balancing stakeholder requests for predictable delivery
Translate business challenges into data-driven solutions aligned with strategy
Own the data science roadmap with leadership, turning priorities into actionable plans
Build, deploy and maintain machine learning models to forecast trends and improve processes
Analyze large datasets to extract actionable insights and present to diverse stakeholders




Advise and continuously improve the data science pipeline to meet analytics needs
Collaborate with business leaders, product teams and engineers to ensure data solutions meet requirements
Stay updated on DS/AI trends to enhance team capabilities
Requisiti fondamentali
5+ years in data science with at least 3 years in a leadership role
Proven track record of solving complex business problems with data
Experience line-managing and growing data scientists
Hands-on credibility in production-quality coding and code reviews
Strong stakeholder management and ability to defend priorities
Good understanding of business operations and aligning DS projects with objectives
Excellent communication skills to translate technical insights for non-technical audiences
Strong analytical and problem-solving abilities
leadership
communication
cross-functional collaboration
Python, R, or Scala
machine learning frameworks (TensorFlow, Scikit-learn)
SQL and handling large data sets

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