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Strong global brand and broad ML/Python leadership requirements, but seniority narrows the candidate pool.
Core ML, Python, and cloud skills are transferable across industries though domain knowledge is advantageous.
Requires advanced ML, production Python, cloud experience and mentorship, creating strict technical filters.
Lead and execute end-to-end data science projects including problem definition, analysis, modelling, implementation and evaluation.
Develop and optimize scalable machine learning models with robust validation and performance monitoring, using Python and cloud platforms like GCP.
Communicate findings clearly to diverse stakeholders and mentor junior data scientists while managing project risks and priorities.
Master's degree or PhD in Data Science, Statistics, Mathematics, Computer Science, or related field; or bachelor's degree with significant equivalent experience.
Significant hands-on experience delivering data science projects from start to finish involving statistical analysis and machine learning.
Proficiency in Python programming and machine learning frameworks, with experience writing maintainable code.
Experience using cloud-based machine learning platforms (e.g. GCP) and communicating with senior technical and non-technical stakeholders.
Senior-level data science professional capable of owning complex projects and driving impact across business functions.
Strong statistical and mathematical expertise combined with advanced machine learning and scalable solution development.
Experienced mentor with proven ability to guide junior data scientists and influence technical decisions in ambiguous environments.