Applied Scientist II
Listed on 2026-08-02
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IT/Tech
Machine Learning/ ML Engineer, Data Scientist, AI Engineer (Applied/Software), Data Engineering
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.
Whatwe do
Our Identity products power intelligent ad buying on TTD. Applied Scientists in the Identity team are end‑to‑end owners of TTD’s identity products. This ownership gives the opportunity to participate in designing, researching, building, and delivering data‑focused and high‑impact products for our stakeholders.
These products are based on large‑scale data in the order of tens of millions of queries per second. Working with such data requires our applied scientists to be at the cutting edge of both data processing frameworks and scalable algorithms.
Our Applied Scientists also serve as ambassadors to our business partners to champion and evolve our identity products as the identity landscape of the open internet changes. They understand the business requirements and current design choices; they communicate effectively with business partners on opportunities and challenges; and they are strategic partners in creating the next generation of identity products.
Applied Scientists contribute to more than our product – they build up our team. We are a team built on generosity and openness, and we expect our Applied Scientists to help make others better and raise the bar for those around them.
What you’ll doSome of the work that you will be doing to help us deliver on our mission is:
- Make significant, self‑directed contributions to components of large and impactful data‑focused projects. You will think beyond just the task at hand to deeply understand the “why” behind what you are doing.
- Work with data from the open internet that is at large scale – think of tens of millions of transactions per second.
- Utilize your strong sense of data intuition. At our scale, many off‑the‑shelf modeling techniques (open source and enterprise) simply don’t work. You will work from first principles and intuition to develop solutions and adapt them to a unique environment.
- Leverage your broad familiarity with basic concepts in probability and statistics, along with exposure to basic foundations of computer science, graph mining, and machine learning.
- Unlock your product‑focused mindset. With your passion and potential, you’ll contribute to the process of discovering what will delight our stakeholders and drive forward one of the world’s largest and most influential industries toward a vision of openness, transparency, and evidence‑based decision‑making.
- Work with confidence and without ego. Our applied scientists have deep knowledge and exercise a high level of leadership in their daily work. You’ll have strongly‑held, defensible ideas, and advocate for what you believe is right. You’ll practice identifying and evaluating trade‑offs, willing to be proven wrong, and be committed to support your fellow teammates.
- Think creatively, not bound by “the way things have always been done.”
- You will have the opportunity, based on your interests and background, to work on problems related to graph mining and graph merging; algorithmic optimization on petabytes of data; and theoretical information approaches for best‑subset selection problems.
We are a global team with different backgrounds, experiences, and perspectives. To complement this team, you…
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