Data Scientist Lead
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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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