The Trade Desk
Staff Applied Scientist, Recommender Systems
The Trade Desk, Denver, Colorado, United States, 80285
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 1 trillion queries per day, our platform operates at an unprecedented scale. We have also built something even stronger and more valuable: an award‑winning culture based on trust, ownership, empathy, and collaboration. 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 self to work every day.
Do you have a passion for solving hard problems at scale? Are you eager to join a dynamic, globally connected team where your contributions will make a meaningful difference in building a better media ecosystem?
ABOUT THE ROLE Data scientists at TTD work closely with engineering throughout the lifecycle of the product, from ideation to productionization and monitoring. 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 and traders.
KEY RESPONSIBILITIES
Design and build large‑scale recommendation systems that guide advertisers and traders toward optimal campaign setups, including audience selection, inventory mix, and bidding strategies.
Develop data‑driven recommendation models that leverage historical campaign performance, marketplace dynamics, and user history to surface intelligent suggestions in real time.
Collaborate with product and engineering teams to integrate recommendation engines into planning, optimization, and reporting tools across The Trade Desk platform.
Build and maintain robust feature pipelines and ranking models that improve recommendation accuracy, diversity, and interpretability.
Partner with downstream teams to define success metrics and design experimentation frameworks (e.g., A/B testing) to evaluate model impact on client and platform performance.
Continuously analyze campaign and marketplace data to identify opportunities for new or improved recommendation products, using user feedback and model diagnostics to drive iteration.
Ensure recommendations are privacy‑safe, scalable, and explainable, aligning with TTD's principles of transparency and trust.
QUALIFICATIONS
Strong foundation in machine learning and deep learning with experience building recommendation or ranking systems.
Solid understanding of forecasting and predictive modeling, especially in dynamic, large‑scale environments such as ad tech, e‑commerce, or digital media.
Passion for translating model insights into practical recommendations that improve advertiser outcomes.
Experience collaborating cross‑functionally with product, engineering, and analytics to ship high‑impact data products.
Strong data intuition and an innovative mindset that drives model development.
Proficiency in Python and Spark; experience running heavy workloads on distributed computing clusters (e.g., EMR, Databricks).
Experience with LLMs and prompt engineering preferred; knowledge of TensorFlow or PyTorch is a bonus.
WHAT YOU BRING TO THE TABLE
BS/MS with 6+ years or a PhD with 4+ years of experience working in a DS or ML role that involves bringing products from ideation to production.
Experience working with LLMs and prompt engineering preferred.
Experience in deep learning, TensorFlow/PyTorch bonus.
The ability to communicate architecture recommendations, ensuring effective execution, and measuring the quality of outcomes.
Experience running heavy workloads on a distributed computing cluster, leveraging technologies like Spark to work with large datasets preferred.
Proficient in Python. Strong Spark skills are a plus.
$137,300 — $251,800 USD
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 accomodations@thetradedesk.com to request an accommodation or discuss any accessibility needs you may require to access our Company Website or navigate any part of the hiring process. When you contact us, please include your preferred contact details and specify the nature of your accommodation request or questions. Any information you share will be handled confidentially and will not impact our hiring decisions.
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Do you have a passion for solving hard problems at scale? Are you eager to join a dynamic, globally connected team where your contributions will make a meaningful difference in building a better media ecosystem?
ABOUT THE ROLE Data scientists at TTD work closely with engineering throughout the lifecycle of the product, from ideation to productionization and monitoring. 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 and traders.
KEY RESPONSIBILITIES
Design and build large‑scale recommendation systems that guide advertisers and traders toward optimal campaign setups, including audience selection, inventory mix, and bidding strategies.
Develop data‑driven recommendation models that leverage historical campaign performance, marketplace dynamics, and user history to surface intelligent suggestions in real time.
Collaborate with product and engineering teams to integrate recommendation engines into planning, optimization, and reporting tools across The Trade Desk platform.
Build and maintain robust feature pipelines and ranking models that improve recommendation accuracy, diversity, and interpretability.
Partner with downstream teams to define success metrics and design experimentation frameworks (e.g., A/B testing) to evaluate model impact on client and platform performance.
Continuously analyze campaign and marketplace data to identify opportunities for new or improved recommendation products, using user feedback and model diagnostics to drive iteration.
Ensure recommendations are privacy‑safe, scalable, and explainable, aligning with TTD's principles of transparency and trust.
QUALIFICATIONS
Strong foundation in machine learning and deep learning with experience building recommendation or ranking systems.
Solid understanding of forecasting and predictive modeling, especially in dynamic, large‑scale environments such as ad tech, e‑commerce, or digital media.
Passion for translating model insights into practical recommendations that improve advertiser outcomes.
Experience collaborating cross‑functionally with product, engineering, and analytics to ship high‑impact data products.
Strong data intuition and an innovative mindset that drives model development.
Proficiency in Python and Spark; experience running heavy workloads on distributed computing clusters (e.g., EMR, Databricks).
Experience with LLMs and prompt engineering preferred; knowledge of TensorFlow or PyTorch is a bonus.
WHAT YOU BRING TO THE TABLE
BS/MS with 6+ years or a PhD with 4+ years of experience working in a DS or ML role that involves bringing products from ideation to production.
Experience working with LLMs and prompt engineering preferred.
Experience in deep learning, TensorFlow/PyTorch bonus.
The ability to communicate architecture recommendations, ensuring effective execution, and measuring the quality of outcomes.
Experience running heavy workloads on a distributed computing cluster, leveraging technologies like Spark to work with large datasets preferred.
Proficient in Python. Strong Spark skills are a plus.
$137,300 — $251,800 USD
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 accomodations@thetradedesk.com to request an accommodation or discuss any accessibility needs you may require to access our Company Website or navigate any part of the hiring process. When you contact us, please include your preferred contact details and specify the nature of your accommodation request or questions. Any information you share will be handled confidentially and will not impact our hiring decisions.
#J-18808-Ljbffr