Data Scientist, AIML Data Scientist

Imagine what you could do here. At Apple new ideas have a way of becoming extraordinary products services and customer experiences very quickly. Do you love thinking analytically Are you passionate about solving complex business problems in a fast-paced environment The AIML Data Operations group engages with teams across Apples ecosystem with the ultimate goal of delivering high-quality annotated data in support of unreleased products and ground breaking AI technology. Within the Data Operations organization the Capacity Planning u0026 Analytics team provides forecasting capacity planning and optimization data products metrics reporting modeling u0026 experimentation and ad hoc are seeking a highly motivated Senior Data Scientist to lead analysis into annotation project trends to uncover patterns in annotator performance task complexity and data characteristics to help optimize task design. You will translate behavioral insights and empirical findings into optimized project structures and workflows and power capacity planning u0026 optimization with quantitative rigorall to ensure we consistently launch projects that are smarter in design faster in execution and uncompromising in quality. You will partner closely with Data Ops Client Engagement Human Factors engineering and annotation customers to collaborate on the most effective methods.

The ideal candidate for this role is an experienced data scientist with deep expertise in analytics and experimentation who excels at building strong cross-functional relationships to drive data-informed decisions across the company and is skilled at partnering with operations and engineering teams to surface and communicate key data insights that improve performance and customer experience at a global scale.

As a Data Operations Capacity Planning u0026 Analytics Data Scientist you will:nnAnalyze trends across projects to identify patterns in annotator performance task complexity and data characteristics that inform more effective project scoping design and guideline development. nEvaluate which tasks and data types benefit most from automation and work with customers to optimize behavioral insights and empirical trends into optimized project structures ensuring our annotation workflows are designed for both efficiency and quality before projects with cross-functional teams to design run and analyze A/B experiments establishing best practices for project to capacity forecasting and optimization by converting quantitative decision-making into forecast drivers and key factors that lead to improving productivity and to development of a holistic view of analyst behaviors across the various platforms and identify synergies that drive a more positive analyst experience and efficiency gains

Bachelors degree in Computer Science Statistics Mathematics Engineering Economics or related field.n4 years of experience in data science with proven skills in developing meaningful and concise analytic objectives from general business goalsnTested capabilities and comfort in scalable schema designs relational database and big data technologies ETL code management and query performance optimizationnMastery in SQL-based languages and proficiency in at least one large-scale data languagesnStrong hands-on experience interpretable with machine learning models and sophisticated analytic solutions using scripting tools such as Python or R

Masters degree or PhD in Computer Science Statistics Mathematics Engineering Economics or related with the deployment of Large Language Models / Generative AI in service of efficiency in operationsnExcellent communication and presentation skills with meticulous attention to detail and the ability to collaborate effectively between business and analytic teams at multiple levels of the organizationnPassion for AIML and Operations with a consistent track record of operational results.