Product Manager - Data Classification

Booking.com

8h

About The Position

At Booking.com, data drives our decisions. Technology is at our core. And innovation is everywhere. But our company is more than datasets, lines of code or A/B tests. We’re the thrill of the first night in a new place. The excitement of the next morning. The friends you encounter. The journeys you take. The sights you see. And the memories you make. Through our products, partners and people, we make it easier for everyone to experience the world.
Our Data and Machine Learning Platform develops platform products that deal with big data, analytics, AI and machine learning. These products are delivered to our internal customers and are at the core of our strategic decisions. The Developer Tooling and Authoring Experience team unifies and simplifies the development environment experiences for data developers – analytics engineers, data scientists, machine learning scientists and engineers, and platform data engineers.
As a Technical Product Manager, you set the product vision, GTM strategy and drive adoption of an enterprise wide data & AI product / asset classification tooling, and its integration with various governance tooling like the enterprise policy platform, the enterprise knowledge graph to offer a consistent way to classify and annotate various data, analytical and AI assets / products, in a consistent fashion, in line with ontologies for each global regulation (f.e. GDPR, CCPA etc.). The product would serve multiple personas from control functions, legal functions to application developers, to data / reporting analysts, to data engineers and ML engineers / scientists and of course governance personas across the business, to enable them leverage the classification tooling to annotate / classify multi-modal asset types, their business context / semantic meaning, which in conjunction with the knowledge graph and policy platform, would collectively govern how BigData gets produced, processed, stored / persisted, consumed and eventually destroyed / deleted, in line with all global compliance and regulatory requirements.
The classification / annotation generated by the product, would also provide valuable business context to these asset types, allowing this semantic context to be leveraged for broader context aware discovery experiences, across platforms (transactional and analytical), enterprise wide
The role would require balancing value elements for the both user segments - the data & AI practitioners of the business as well as the compliance / control / legal functions. You would be passionate about identifying opportunities for your product(s), be deeply passionate about the compliance challenges around multi-modal data processing the enterprise and our users face today, understand how AI systems available at our disposal today can help bridge a lot of the these gaps, delighting our platform users by addressing the most pressing classification and policy issues - across the disparate multi-modal data processing pathways enterprise wide.
The role would require familiarity with distributed policy enforcement and access management systems, a deep and wide understanding of how data gets captured across various funnels enterprise wide and how and in what context the same gets processed as it moves through systems / platforms enterprise wide.
User-focused individual who keeps the customer at the heart of everything they do, while having strong commercial awareness.
Data-driven. Base your decisions on facts rather than opinions.
A go-getter who isn’t afraid to roll up sleeves and dives into a project to achieve success by problem solving.
Passionate about data & machine learning and building a platform that can be leveraged by the whole company. Constantly looking for ways to improve and streamline the capabilities.
Open-minded team player with excellent communication skills.
Agile and innovative with the tenacity to thrive in a constantly changing environment.
Self-motivated and results-driven with a take charge attitude to manage the full development cycle of a product.
Friendly, knowledgeable, and motivational to others. Open to diversity in all shapes and sizes.

Requirements

• Experienced with distributed data & AI Platforms, including wide and deep understanding of various distributed data processing and AI processing capabilities. Familiar with data processing in production, at scale. Understanding of batch and stream processing, as well as native cloud solutions powering such pathways.
• Experience with Graph database systems and understanding of how LLMs leverage context windows in custom prompts, sourced from a variety of input vectors, to fine tune custom LLM outputs.
• Solid understanding of various data, analytical and AI assets / products (from datasets > workflows / pipelines > metrics > reports > prompts > features > agents) and how their dependencies are intertwined in a distributed data & AI platform.
• Solid understanding of the value proposition of semantic views and the context it adds to abstract consumption complexity for consumers, while forging re-usability of trusted asset types across the enterprise.
• Strong understanding of asset discovery funnels across various journeys on distributed data & AI platforms, across a wide range of personas, and how classification feeds semantic context of various assets, to make such discovery journeys more relevant, context aware.
• Ability to identify core success metrics across various parts of data production and consumption funnels
• Experience with public Cloud offerings (AWS and GCP) and building on top of cloud platform primitives.
• 6+ years of experience in a Product Management, Engineering or Technology Strategy role.
• Good knowledge of data science / analytics techniques
• Master of making data-driven decisions, managing backlog, setting and monitoring KPIs
• Experience with stakeholder management (finance, budgeting, team management, recruitment, external customers).
• Strong teamwork and collaboration skills are essential.
• Ability to rapidly adapt to the evolving technology landscape, keep abreast of the rapidly evolving data and AI industry are paramount.

Nice To Haves

• Experience with web analytics software such as Google Analytics is a plus
• Experience running A/B tests (or exposure to A/B testing concepts) is a plus
• Previous involvement with high traffic (50,000+ visitors per day) on the platform development side, preferably E-commerce is a plus

Responsibilities

• set the product vision
• GTM strategy
• drive adoption of an enterprise wide data & AI product / asset classification tooling
• integration with various governance tooling like the enterprise policy platform, the enterprise knowledge graph to offer a consistent way to classify and annotate various data, analytical and AI assets / products, in a consistent fashion, in line with ontologies for each global regulation (f.e. GDPR, CCPA etc.)
• enable them leverage the classification tooling to annotate / classify multi-modal asset types, their business context / semantic meaning, which in conjunction with the knowledge graph and policy platform, would collectively govern how BigData gets produced, processed, stored / persisted, consumed and eventually destroyed / deleted, in line with all global compliance and regulatory requirements.

Benefits

• Medical, life, and disability insurance
• Annual paid time off and generous paid leave scheme including: parent, grandparent, bereavement, sick, and care leave
• Industry leading product discounts for yourself, friends, and family, including automatic Genius Level 3 status and annual Booking.com wallet credit (keep this part, for internal JDs only)
• Free access to online learning platforms, mentorship programs, and a complimentary Headspace membership
• Collaborative, friendly and diverse culture
• Referral Program

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees