Staff Data Scientist-B2B Recommender Systems

The Trade Desk, Inc. • New York, NY • 6h ago

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 over1 trillionqueries per day, our platformoperatesatan 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 authenticselvesto work every day.Do you have a passion for solving hard problemsatscale? Are you eager to join a dynamic, globally connected team where your contributions will make a meaningful difference in building a better media ecosystem?Come and seewhy Fortune magazine consistently ranks The Trade Desk among the best small-medium-sized workplaces globally.ABOUT THE ROLEData scientists at TTD work closely with engineering throughout the lifecycle of the product, from ideation toproductionizationand monitoring. Our data scientists are end-to-end owners. You willparticipateactively in all aspects ofdesigning, researching, building, and delivering data-focused products for our clients and traders.Thisparticular rolefocuses on developing forecasting and recommendation models that power intelligent planning, pacing, and optimization across the platform.You will build systems that help advertisers make data-informed decisions on audienceselection, inventory allocation, and bidding strategy. Accurate forecasting and recommendation are essential for giving real-time feedback to our clients, improving campaign outcomes, and driving media efficiency at scale. The main job directions include:- Design and build large-scalerecommendation systemsthat guide advertisers and traders towardoptimalcampaign setups - including audienceselection, inventory mix, and bidding strategies. - Developdata-driven recommendation modelsthatleveragehistorical campaign performance, marketplace dynamics, anduser historyto surface intelligent suggestions in real time. - Collaborate with product and engineering teams tointegrate recommendation enginesinto planning, optimization, and reporting tools across The Trade Desk platform. - Build andmaintainrobustfeature pipelines and ranking modelsthat improve recommendation accuracy, diversity, and interpretability. - Partner with downstream teams to definesuccess metricsand designexperimentation frameworks(e.g., A/B testing) to evaluate model impact on client and platform performance. - Continuously analyze campaign and marketplace data toidentifyopportunities for new or improvedrecommendation products, using user feedback and model diagnostics to drive iteration. - Ensure recommendations areprivacy-safe, scalable, and explainable, aligning with TTD's principles of transparency and trust.WHO WE ARE LOOKING FOR- Strong foundationin machine learning and deep learning, with experience developing and deployingrecommendationor 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. - Possessesa keen sense of data intuition and the ability to innovate in the field of model development.Hasa data driven mindset and usesdata to drive your model development plan.WHAT YOU BRING TO THE TABLEWe do not expect you to know every technology we use when you start at TTD. What we care most about is that you can learn quickly and solve complex problems using the best tools for the job. However, we find that the most successfu

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