Lead Product Data Scientist

Overview

As Lead Product DataScientist, you’ll shape production-grade data science and optimization solutions within a cross-functional product squad. You’ll translate business challenges into analytical and ML-enabled decisions that scale in cloud environments. The role emphasizes delivering robust, production-ready models and data pipelines that drive real-world outcomes. You’ll collaborate with software engineers, product managers and stakeholders to balance fast delivery with long-term value, making an impact across the product lifecycle.

Responsibilities

• Identify opportunities where data science and optimization improve decision-making.
• Perform analytical investigations and visualise data to uncover insights and evaluate solutions.
• Develop and validate ML and optimization models in Python.
• Build scalable, production-ready features following software engineering best practices.
• Create automated, robust data processing and quality pipelines.
• Integrate models into orchestration and cloud deployment environments.
• Implement testing, monitoring, logging and error handling for reliability.
• Gather requirements from stakeholders and demonstrate value to support adoption.
• Contribute to product roadmap and balance short-term delivery with long-term value.
• Collaborate in an Agile environment with code reviews, documentation and continuous improvement.

Key requirements

• Strong expertise in machine learning, optimization or operational research
• Proficiency in Python and libraries (pandas, NumPy, scikit-learn)
• Experience applying analytical methods to real-world business problems
• Strong SQL and data engineering capabilities
• Experience with cloud platforms, ideally AWS
• Familiarity with Git and software development best practices
• Experience writing and maintaining automated tests
• Excellent communication and stakeholder management skills

• effective communication
• problem-solving
• prioritisation
• Python
• pandas
• NumPy

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