At Apple, we focus deeply on our customers’ experience. Apple Ads brings this same approach to advertising, helping people find exactly what they’re looking for and helping advertisers grow their businesses. Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass. Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone. In this role, you will cultivate a deep understanding of the relationship between our machine learning models and business/customer outcomes. Evaluate opportunity areas and create roadmaps for improving the machine learning models underlying our search and recommendation systems. Develop success metrics for efforts to improve our models. Work with the industry’s best engineers, data scientists, and researchers to create and assess A/B experiments on new models. Work with privacy, engineering, and business teams to develop novel privacy-preserving strategies for collecting information for use in our models. Experience working on search and/or recommendation systems or another consumer product that uses machine learning is strongly preferred, and experience in digital advertising is a plus.

DESCRIPTION

• Act as product owner for the machine learning models underlying our privacy-preserving search and recommendation systems. - Define success criteria and product requirements for our models by cultivating a deep understanding of the relationship between our models and business / customer outcomes. - Formulate clear and measurable hypotheses for how to improve success metrics, work with engineering and data science teams to test hypotheses, and make decisions based on experiment results. - Synthesize insights from data analysis, customer calls, and sales feedback into clear and concise opportunity areas and develop short-term and long-term roadmaps around these opportunity areas. - Collaborate with engineering, data science, and research teams to develop, launch, evaluate, and improve search and recommendation system models. - Collaborate with privacy, engineering, and business teams to develop novel privacy-preserving strategies for collecting information for use in our model. - Produce high-quality 1-pagers, product requirements, and presentations, to convey opportunity areas, experiment results, recommendations, and product strategy to cross-functional teams and leadership on a regular basis.

MINIMUM QUALIFICATIONS

• Product Management experience.
• Proficiency in SQL and experience in analyzing complex, large-scale data sets to form hypotheses, evaluate experiment results, justify product opportunities, and measure success.
• Exceptional written and verbal communication skills, with the ability to clearly and concisely convey results and opportunity areas to cross-functional teams and leadership.
• Proven experience in defining measurable and interpretable success metrics and rallying cross-functional teams to achieve them.
• Customer-centric attitude, with the ability to define and prioritize use cases and customer objectives.
• Strong track record of collaborating with engineering and data science teams to develop, launch, and improve machine learning models.
• Excels in a fast-paced environment with a high degree of ownership and accountability.

PREFERRED QUALIFICATIONS

• 3+ years of Product Management experience.
• Previous experience working on search and/or recommendation systems or another consumer product that uses machine learning.
• Previous experience working in digital advertising and/or familiarity with digital advertising concepts through usage of ad platforms.

Please refer the Job description for details