Job Description

The Automation organization enables and measures the unified customer journey, intelligently empowering customers through Square's ecosystem of products. We are using Engineering, Data Science/Analytics, and Machine Learning/AI to do five core jobs for our customers: (1) Unify the customer journey through data and messaging; (2) Automate channels for connecting with prospects and customers; (3) Personalize platforms and products; (4) Measure across the customer life-cycle; and (5) Promote innovation and product development at a low-cost.

As the Product Manager for Personalization and Recommendations team, you will guide important Machine Learning/AI and Data Science programs from creation through execution. You will focus on building ML/AI-based products for providing acquisition marketing recommendations, customer lifecycle personalization and human outreach recommendations. You will be in a unique position of having multiple teams as your core customers (Global Marketing, Product and Lifecycle Platform, Sales, and Account Management). You will lean on an accomplished Machine Learning Engineering team to ensure that our products provide remarkable experience and accuracy and promote Square's growth. You will need strategic thinking, methodical execution, and superb partner management in addition to expertise in Personalization, Recommendations, and Machine Learning Infrastructure. If you're looking for the rare opportunity to make a foundational impact on Square's go-to-market strategy and develop growth ML products, you will find this role compelling and rewarding.

You will: 

• Set the vision, roadmap, and direction for the Personalization and Recommendation products
• Lead the planning, scoping, and prioritization of projects to achieve all of our goals
• Gather requirements, determine features, write product specs, refine feedback, help write test plans, manage the backlog, and ship quickly
• Represent the team with partners and senior company leaders to align resources and prioritization
• Drive accuracy of ML/AI products leading to their enterprise-wide adoption
• Educate others on ML/AI products and capabilities
• Foster an environment that enables the Machine Learning Engineering team to execute quickly while maintaining a high standard for quality

Qualifications

You have:

• A Bachelor's Degree, ideally in a technical discipline, or equivalent work experience
• 3 years of experience as a Product Manager
• 3 years of experience building ML/Data Science Products
• Understanding of modern Machine Learning/AI approaches.
• Deep knowledge of Personalization, Recommendation and Optimization capabilities and processes, especially for Growth/Marketing use cases.
• Knowledge of Data Infrastructure and foundational processes
• Navigated difficult situations with competing partner needs and across multiple audiences (individual contributors, managers, executives)
• Experience with customer empathy and experience shaping product direction and execution based on customer needs

Additional Information At Square, we value diversity and always treat all employees and job applicants based on merit, qualifications, competence, and talent. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. Applicants in need of special assistance or accommodation during the interview process or in accessing our website may contact us by sending an email to assistance(at)squareup.com. We will treat your request as confidentially as possible. In your email, please include your name and preferred method of contact, and we will respond as soon as possible. PERKS At Square, we want you to be well and thrive. Our global benefits package includes:

• Healthcare coverage
• Retirement Plans
• Employee Stock Purchase Program
• Wellness perks
• Paid parental leave
• Paid time off
• Learning and Development resources