Product Manager, Support Products - Machine Learning and Data Platform

Airbnb is a vision and mission driven company. Our Product Managers embody this culture and mindset. Product Managers here imagine the ideal end state for our community (guests and hosts) first and work backwards from it, challenging all current assumptions. They champion a winning strategy and leverage metrics to ensure we are making progress against it. They partner with talented cross-functional team members (across engineering, design, data science, etc.) and lead teams to execute upon a shared vision. They are incredibly hands on and are not afraid to roll up their sleeves to get the right outcome for our community.  We are looking for leaders who want to join us in this journey to accomplish our mission of creating belonging everywhere.

About Support Products

Success is about delivering great customer service for our users - both self help and human support - throughout their Airbnb journey. We believe that service will be a major differentiator and driver of Airbnb’s global success and growth. We’re building a technology platform that supports Airbnb as it scales, delivers an exceptional level of customer service and improves efficiency and the customer service agent experience.  

About the Role

The Airbnb Support Products Sr. Technical Product Manager, Machine Learning and Data Platform will be responsible for leading the Community Support Products Machine Learning and Data Platform products at Airbnb. Community Support (CS) is a global business unit that supports our millions of guests and hosts who take trips and join experiences around the world every year. 

Great products and experiences are built on robust data, and many stakeholders, from the developers of a service, to their managers, compliance teams, and executives need to know how to leverage this rich data to drive impact effectively and efficiently. A successful candidate will work collaboratively with two critical platform teams - the CS Data Platform Team and CS Core Machine Learning Team to drive exceptional experiences for the Airbnb Community.  

The CS Data Platform Team manages the flow and insights of our intelligent data within Airbnb’s Community Support business, securing it, and ensuring the appropriate users can access it and leverage it effectively. This team is also the pipeline to the reporting systems trusted by customers, executives and stakeholders. We are successful when we make this data easy to consume and use for product teams and for engineers. 

The Core Machine Learning Team is a world-class team of AI and ML data engineers who leverage complex algorithmic models to drive intelligence in every interaction along our Community’s journey. The exciting road ahead is built on an intelligent support platform that leverages our unique data in ways that drive exceptional experiences. 

This successful candidate will also work collaboratively with business stakeholders and operation teams, to drive end to end product and technical solutions to meet the needs of the Community Support operations and ongoing business needs. 

If you are the type of person that feels a personal stake in everything that you work on, have a strong sense of ownership, a love for data, enjoy working with complex technologies know how to foster strong relationships and build trust, and work for the success for the entire team - then we look forward to meeting you!

Responsibilities

• Deeply understand the need for data and machine learning and how it can be applied intelligently for CS within Airbnb
• Drive product and technical requirements, strategy and end results for data collection, processing, publishing, pipelining, and ML models within Airbnb
• Keep up with cutting edge technologies, (especially open source projects) and new technological and machine learning innovation that can potentially be applied to Airbnb CS use-cases
• Define and drive technical product scope and prioritization and be flexible to iterate/change per latest developments to meet agreed upon deadlines and business needs
• Maintain product backlog, drive product roadmap and own prioritization process of CS data product solutions based on business value and customer impact
• Demonstrate ability to translate business requirements and work with various levels of business stakeholders to create innovative scalable solutions
• Define the success metrics and SLAs by partnering with other cross functional leaders in Support Products while keeping it up to date and relevant
• Evaluate new product opportunities (both buy and build solutions) and bring forward proposals and influence to expand product and business capabilities with data and intelligent automation at the forefront 
• Leverage and instrument data-driven experimentation and measurement frameworks to track and report product success or lack of thereof
• Work closely with all business, ops, and product stakeholders to ensure successful end-to-end delivery of data and ML products
• Work closely and collaboratively with CS operations and engineering teams to ensure reliable operations and SLAs are met or exceeded  
• Create data strategies and programs for the long-term success of business teams and ensure engineering teams are positioned to deliver results
• Present overall product roadmap status to the business and Support Products leadership on an ongoing basis
• Closely coordinate cross-functional global operations, Support Products, and IT teams to ensure close alignment, clear dependencies, and streamlined execution.
• Develop key interdependent roadmap sequencing and plans in support of Support Product leadership

Qualifications

• 10+ years experience in Product, Technical Program or Project Management, or similar role leading a cross-functional technical team
  BA/BS degree is required. Concentration in Computer Science or a related technical discipline is preferred
• 3+ years of technical product management
• Exceptional collaboration, partnership and influencing skills with the ability to work in a global environment across multiple locations and time zones to drive consensus in cross-functional teams
• Demonstrated interpersonal skills to interface well with ops and business partners at all levels
• Outstanding written and verbal communication ability to a diverse stakeholder audience, including a global team of C-level executives, product, and technical stakeholders
• Strong customer engagement and relationship management skills
• More than comfortable in an ambiguous matrixed organization
• Strategic platform and system thinker who can balance big picture strategy with detailed, flawless execution
• Creativity and ability to work independently with limited guidance with proven ability to create structures and develop operational concepts
• High tolerance for ambiguity and ability to perform under pressure to meet deadlines
• Experience developing roadmaps and long-term data-driven strategies for improving operations, data platform efficiencies - all without sacrificing quality
• Deep understanding of software development for machine-learned products and services
• Self-sufficient in analyzing and drawing conclusions about the quality and product opportunity from raw and refined product data
• Self-motivated and proactive, with demonstrated creative and critical thinking capabilities
• Innate capability to, directly and indirectly, lead teams through success
• Strong technical project/product management experience in large scale systems, Linux/server operating systems, databases, cloud computing, big data, networking, and bonus points for past programming experience.
• Prior PM or engineering experience in speech recognition, natural language understanding, search, data pipelines, and/or A/B testing a big plus

The ideal candidate will have a strong technical background in one or more of the following areas:

• Data architecture
• Hadoop, Spark, Kafka, large scale real time and batch processing
• Machine learning, artificial intelligence, feature engineering, model lifecycle management and deployment
• Query building, Presto, HIVE, SQL, metadata, data wrangling,
• Data warehouse, data stores, aggregations, data architecture, data integrations
• Data quality, SLAs, customer engagement
• Containerization - Kubernetes, agile, workflow, resource management
• Scalable API infrastructure and general APIs
• Data assets, data governance, storage and sharing
• User experiences, user access, security, query builder, interface and information architecture

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