Aiml – Senior Data Science Manager – Aiml Data

Aiml – Senior Data Science Manager – Aiml Data

Requirements

• 10+ years of relevant work experience.
• 6-8 years of experience managing a team of data scientists or related roles, including delivering successful projects or initiatives that achieved measurable outcomes.
• Skilled in mentoring and developing junior talent while fostering a collaborative and innovative environment.
• Experienced in effective collaboration with cross-functional teams, including product, engineering and tooling, to accomplish shared goals.
• Proficiency in data science, machine learning, and analytics, including statistical analysis, data quality evaluation, prompt engineering, and fine-tuning models.
• Strong hands-on expertise in technical execution, including building and deploying models, developing pipelines, and debugging complex data processes.
• Experienced in designing, conducting, analyzing, and interpreting experiments and investigations.
• Expertise in setting strategic directions and integrating new technologies and methodologies into workflows to improve team efficiency and deliver significant business impact.
• Proven capability to lead multiple large-scale, high-impact projects concurrently, balancing strategic oversight with necessary detailed execution to ensure timely and successful delivery within scope.

Responsibilities

• Research and develop evaluation methods to improve the quality of Apple user-facing products, such as Siri, Search, and Apple Intelligence.
• Work with evaluation/experimentation engineering teams to get your methodological developments translated into technologies that product engineering will use every day.
• Work with large, complex data sets.
• Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed.
• Conduct analysis, including data collection and quality control, requirements specification, processing, and presentations.
• Build and prototype analysis pipelines iteratively to provide insights at scale.
• Develop comprehensive knowledge of product data structures and metrics, advocating for changes where needed for product development.
• Partner closely with product engineering teams on core machine learning algorithms and user experience evaluations.

Preferred Qualifications

• Advanced degree in a quantitative field such as Statistics, Operational Research, Bioinformatics, Economics, Psychology, Computer Science, Sociology, Mathematics, Physics, or a similar quantitative field.
• Exceptional communication skills with the ability to emphasize statistical rigor and principled methodologies, including presenting analytical findings that influenced key leadership decisions such as strategic pivots or resource allocation.