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Staff Data Scientist

Company: The Trade Desk
Location: New York
Posted on: January 27, 2023

Job Description:

The Trade Desk is a global technology company with a mission to create a better, more open Internet for everyone through principled, intelligent advertising.

Handling over 600 billion queries per day (more than 100X the query volume of search globally), our platform operates at unprecedented scale. We have also built something even stronger and more valuable: an award-winning culture based on trust, empathy, collaboration, and ownership. By working together across typical dividing lines, we are better as a team than any of us could be apart.

Do you have a passion for solving hard problems at scale? Are you eager to join a trust-based, globally-connected team, where your contributions will make a meaningful difference?

Come and see why Fortune Magazine consistently ranks The Trade Desk among best small-medium sized workplaces globally.


* Our Data Scientists are end-to-end owners. You will participate actively in all aspects of designing, researching, building, and delivering data-focused products for our clients. As a Staff Data Scientist, you will contribute meaningfully through leading others.
* Our Data Science team is embedded into nearly a dozen individual, mission-focused engineering teams working across a wide spectrum of technological and scientific challenges.
* You will have the opportunity, depending on your interests and background, to work on problems related to natural language processing and machine learning over hundreds of millions of web pages; graph mining and algorithmic optimization on petabytes of data; and causal inference with missing data - to name a few.
* Data Scientists contribute to more than our product - they build up our team. We are a team built on a foundation of generosity and openness, and we expect our Data Scientists to help make others better and raise the bar for those around them.


* You have a sustained track record of making significant, self-directed, and end-to-end contributions to complex, multi-layered, impactful machine learning projects. You think beyond just the task at hand to deeply understand the 'why' behind what you are doing and anticipate problems that may be several degrees removed from obvious requirements.
* You make your team better by proactively advocating for and driving improvements not just to what the team produces, but also the ways in which the team works.
* You have a strong sense of data intuition. At our scale, many off-the-shelf modeling techniques (open source and enterprise) simply don't work. You are able to work from first principles and intuition to develop solutions and adapt them to a unique environment.
* You are a broadly skilled data scientist with deep expertise working with embedded models in always-on production systems and working across a variety of technologies and data sources.
* You have a product-focused mindset. You have the passion and ability to contribute to the process of discovering what will delight our clients and push forward one of the world's largest and most influential industries toward a vision of openness, transparency, and evidence-based decision-making.
* You work with confidence and without ego. Our data scientists have deep knowledge and exercise a high degree of leadership in their daily work. You have strongly-held, defensible ideas, and advocate for what you believe is right. You are also adept at identifying and evaluating trade-offs, willing to be proven wrong, and quick to walk through fire to support your fellow teammates.
* You value, seek out, and foster diversity. We are a global team from many diverse backgrounds, with different experiences and perspectives. To complement this team, you will welcome ideas that are different from your own and be skilled at finding and building from common ground.
* You are a creative thinker, not bound by "the way things have always been done." What you know is less important than how well you learn and innovate. We don't need data scientists who know all the answers; we need data scientists who can invent the answers no one has thought of yet, to the questions yet to be asked.


* You have an abundance of intellectual curiosity and are enthusiastic to learn (and teach) new technologies / techniques.
* You are you comfortable working on an agile, distributed team spanning multiple time zones and continents.
* You are able to communicate effectively across both technical and non-technical audiences.
* Preferred, a BS/MS with 12 years or a PhD with 8+ years of experience working in a data-driven role. What is most important to us is what and how you can contribute though which is why our consideration is not limited by the level of education you have.
* You make effective use of big data technologies such as Spark and AWS, are able to write efficient SQL, and are proficient in one or more of the following programming languages: R, Python, Java, or Scala. Variety of technical challenge is one of the best things about working at The Trade Desk as a data scientist though which is why we do not expect you to know every technology we use when you start. What we care about is that you can learn quickly and solve complex problems using the best tools for the job.


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.

Keywords: The Trade Desk, New York , Staff Data Scientist, Other , New York, New York

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