Data Scientist II

The Trade Desk is changing the way global brands and their agencies advertise to audiences around the world. How? With a media buying platform that helps brands deliver a more insightful and relevant ad experience for consumers –– and sets a new standard for global reach, accuracy, and transparency. We are proud of the culture we have built. We value the unique experiences and perspectives that each person brings to The Trade Desk, and we are committed to fostering inclusive spaces where everyone can bring their authentic selves to work every day.

So, if you are talented, driven, creative, and eager to join a dynamic, globally-connected team, then we want to talk!

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.

 

WHAT YOU WILL BE DOING:

• 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

 

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 are familiar with one of the deep learning frameworks (e.g., Tensorflow, Pytorch), knowledge of inference optimization is a plus
• You have experience with big data technologies such as Spark, AWS and are able to write efficient SQL
• You have experience in multiple programming languages (Python, Scala, Java, etc.) and are fluent at some selections of those
• Bonus if you have experience in Adtech or recommendation systems
• Bonus if you have experience in Look-a-Like modeling or similar algorithms

 

The Trade Desk does not accept unsolicited resumes from search firm recruiters. Fees will not be paid in the event a candidate submitted by a recruiter without an agreement in place is hired; such resumes will be deemed the sole property of The Trade Desk. The Trade Desk is an equal opportunity employer. All aspects of employment will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.