Applied Scientist II

Responsibilities

• Be an intellectually generous and collaborative team member
• Develop end-to-end machine learning prototypes that could scale to run in a production environment
• Contribute meaningful improvements to existing machine learning models through carefully directed research
• Maintain a focus on shipping product, understanding that oftentimes done is better than perfect
• Derive actionable insights from massive data sets with minimal support
• Provide input into the collection of new data sources and the refinement of existing ones to improve analysis and model development
• Become an expert on TTD's client-facing platform
• WHAT YOU BRING TO THE TABLE:
• NON-TECHNICAL QUALIFICATIONS:
• You are enthusiastic to learn (and teach) new technologies, machine learning techniques, and advancements in the adtech industry
• You are comfortable working on an agile, distributed team spanning multiple time zones and continents
• You have an abundance of intellectual curiosity
• You are able to deliver a convincing story derived from the data sets to both a technical and non-technical audiences
• You have experience working closely with engineering team to bring ideas into real product
• Experience in digital advertising and/or recommendation system, relevant experience in recall / ranking is a plus
• TECHNICAL QUALIFICATIONS:
• A relevant scientific and mathematical education (Masters and/or PhD welcome) with 5+ years of professional or academic experience in a data driven role working with massive data sets
• You have a solid understanding of statistical machine learning and optimization techniques as well as the ability to derive actionable insights from massive data sets
• You have experience recall/matching/retrieval algorithms
• You have experience in Adtech or recommendation systems
• You are familiar with one of the deep learning frameworks (e.g., Tensorflow, Pytorch, MXNet), knowledge of inference optimization is a plus
• You have experience with big data technologies such as Spark, AWS, Hadoop, Hive and are able to write efficient SQL
• You have experience in multiple programming languages (Python, R, Scala, Java, etc.) and are fluent at some selections of those
• As an Equal Opportunity Employer, The Trade Desk is committed to creating an inclusive hiring experience where everyone has the opportunity to thrive.
• Please reach out to us at accommodations@thetradedesk.com to reques

Additional Information

The Trade Desk is a global technology company and the world's leading independent platform for digital advertising, with nearly 4,000 employees across more than 30 offices. Our technology helps advertisers reach the right audiences across the open internet - from streaming TV and podcasts to mobile apps, news, and more. Advertising powers the content people love. By making it more transparent, effective, and responsible, we help support trusted journalism, quality entertainment, and creators worldwide. The world's brands and agencies rely on us to reach their customers and grow their businesses responsibly. The scale of our platform brings unique technical challenges - from processing massive datasets in real time to building systems that operate reliably on a global scale. When you work here, your impact is worldwide. We welcome diverse perspectives, encourage curiosity, and build teams that learn from one another. If you're driven to solve meaningful challenges, we'd love to meet you. WHO WE ARE LOOKING FOR: At The Trade Desk, the Data Science team is responsible for transforming our hundreds of terabytes of Real-Time Bidding (RTB) advertising auction data into actionable intelligence, using advanced modelling and optimization algorithms. Our mission is to develop new and powerful means of growing the value of our client's campaigns across millions of web-based publishers. Our team believes in innovation that contributes to our product. In this role, you will be a key member in the development of entirely new data products and the improvement of existing ones, all while using world-class machine learning. You will interact primarily with our product, trading, and engineering teams to oversee the implementation of your data products. Your ideas and research will contribute directly to our client facing product.

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