ABOUT THE ROLE
Our team is responsible for the development of algorithms that help
power our Audience Targeting with the ultimate goal of helping
thousands of customers run effective advertising campaigns. Many of our
problems involve deep learning algorithms to train and develop inference
at scale. Some of the challenges include the parsing of noisy labels and
data, working with large output spaces (thousands of labels), and
unreliable ground truth.
Data scientists on our team work closely with engineering throughout the
lifecycle of the product, from ideation to productionalization 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.
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. As a Data Scientist, you will contribute meaningfully
through leading others.
WHO WE ARE LOOKING FOR
 You have a sustained track record of making significant, self-directed
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 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
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 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.
WHAT YOU BRING TO THE TABLE
We 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 successful candidates typically come in with something like the
following experience:
 BS/MS with 4+ years or a PhD with 2+ years of experience working in a
DS or ML role that involves bringing products from ideation to
production.
 Experience in deep learning, TensorFlow/PyTorch preferred.
 The ability to communicate with diverse stakeholders, making
architecture recommendations, ensuring effective execution, and
measuring quality of outcomes.
 Experience running heavy workloads on a distributed computing
cluster (especially EMR or Databricks), leveraging technologies like
Spark to work with large datasets preferred.
 Proficient in at least two of: R, Python, Java, or Scala. Expert at one of
those. Strong SQL skills.
 Proficient in software engineering concepts like containerization and
version control preferred.

Job Title: Data Scientist II

Location: 400 Spectrum Center Drive, Suite 550, Irvine, CA 92618

*Telecommuting permitted: work may be performed within normal commuting distance from The Trade Desk, Inc. office in Irvine, CA.

Job Duties: Design, implement, and optimize scalable graph-based algorithms to enhance internal graph products. Optimize large-scale algorithmic systems operating on terabyte-scale datasets using distributed computing frameworks. Develop custom data science solutions from first principles, leveraging advanced techniques in probability and statistics, machine learning, and graph mining, especially in contexts where off-the-shelf models are ineffective. Analyze large datasets and build statistical models at scale on top of terabytes worth of data to generate actionable insights for products improvement. Conduct scientific analysis to validate third-party data and evaluate whether they are useful for products. Conduct best-subset selection using information theory-based approaches to enhance targeting and performance strategies. Automate and monitor workflows using orchestration tools (e.g. Apache Airflow) to ensure reliable data pipeline execution. Own the end-to-end data products lifecycle, including identifying research questions, exploratory data analysis, methods design, development, testing, deployment, maintenance, and presenting results to relevant stakeholders. Collaborate with cross-functional teams to ensure technical design, implementation, and delivery of data science projects align with business objectives and product roadmap.

Salary: $130,270 - $170,600 / year

Job Requirements: Bachelor's degree (U.S. or foreign equivalent) in Computer Science, Data Science, or related field and four (4) years of experience in the job offered or related role. Must have four (4) years of experience with: one or more programming languages; SQL; cloud computing platforms; version control systems and CI/CD pipelines; data analysis and visualization for large-scale datasets; building and evaluating machine learning models; applying probability and statistical methods to build and evaluate data-driven products; and Agile. Must have two (2) years of experience with: developing scalable graph algorithms; large-scale graph mining; distributed computing frameworks including Spark; and workflow orchestration tools.

#LI-DNI

What we do  

Our Identity products power intelligent ad buying on TTD. Our Applied Scientists in the Identity team are end-to-end owners of TTD’s identity products. This end-to-end 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 that are in the order of tens of millions of queries per second. Working with such large-scale data requires our applied scientists to be at the cutting edge of both the data processing frameworks as well as scalable algorithms.  

Our Applied Scientists also serve as an ambassador 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 a foundation of 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 do: 

Some 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 will welcome ideas that are different from your own and be well-versed in building from common ground to value, seek out, and foster invisible and visible dimensions of diversity. 

Who you are: 

Our culture is much deeper than just having fun together (though we do that well too). We take pride in our technical team members being trust-builders, generous givers, scrappy problem solvers, and gritty pursuers of excellence. You do not have to meet all the requirements below, but we believe that people who meet most of them will have a higher likelihood of succeeding in this role: 

• You have an abundance of curiosity and are eager to learn (and teach) new technologies / techniques.  

• You are 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.  

• You have practical experience with big data technologies such as Spark, AWS, Databricks,  

• You are able to use a querying language such as SQL,  

• You have practical experience in one or more of the following programming languages: Scala, Python, Java, or R.  

• You have practical experience in large-scale fraud prevention, graph mining, and data quality initiatives. 

• You have 2+ years of experience working as a professional applied/data scientist/analyst or in a research role (includes PhD or post-doc experience in a quantitative discipline). 

• You have a Bachelor’s/Master’s/PhD level degree in a quantitative discipline. Not everyone has the same level of access to opportunities. What is most important to us is what and how you can contribute, which is why our consideration is not limited by the level of education you have. 

• A variety of technical opportunities is one of the best things about working at The Trade Desk as an Applied Scientist, 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 find solutions to complex problems using the optimum tools for the job. What you know is less important than how well you learn and innovate. We are not seeking engineers who know all the answers; we need engineers who can invent answers no one has thought of yet and find answers to the questions yet to be asked.   

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
• Experience in digital advertising and/or recommendation system, relevant experience in recall / ranking is a plus

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 have experience recall/matching/retrieval algorithms
• You have experience in Adtech or recommendation systems
• You are familiar with one of the deep learning frameworks (e.g., Tensorflow, Pytorch, MXNet), knowledge of inference optimization is a plus
• You have experience with big data technologies such as Spark, AWS, Hadoop, Hive and are able to write efficient SQL
• You have experience in multiple programming languages (Python, R, Scala, Java, etc.) and are fluent at some selections of those

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.

We are looking for a Lead Staff Data Scientist to join the Marketplace Quality Engineering (MQE) team. MQE is a cross-functional team responsible for the integrity, performance, and trustworthiness of The Trade Desk’s inventory marketplace. We build systems that detect and prevent fraud, measure and improve inventory quality, and optimize marketplace dynamics to deliver better outcomes for advertisers, publishers, and consumers. 

In this role, you will provide technical and strategic leadership within MQE by defining data science roadmap and execution plans, owning end-to-end development of advanced modeling, analytical, and measurement systems, and partnering closely with engineering, product, and business leaders to translate complex requirements into trusted, scalable solutions. 

WHAT YOU’LL DO 

Technical Ownership 

• Own the data science vision and roadmap for MQE initiatives, aligning technical direction with strategic goals and industry trends. 

• Design, build, and productionize statistical and machine learning models to detect fraud, invalid traffic, and low-quality inventory in adversarial, large-scale environments. 

• Define and maintain metrics, experimentation procedures, and monitoring systems to ensure long-term performance. 

• Develop analytical and explainability frameworks that provide clear visibility into how quality initiatives impact inventory supply, advertiser spend, and marketplace dynamics. 

Cross-Functional Impact 

• Collaborate with product and business stakeholders to translate analytical insights into clear, defensible decisions and marketplace enforcement strategies. 

• Partner closely with engineering to deploy scalable, performant models. 

• Anticipate emerging marketplace risks and proactively develop data-driven solutions to protect marketplace integrity. 

Leadership & Mentorship 

• Act as a staff-level technical leader, setting standards for analytical rigor, model evaluation, and scientific best practices across MQE. 

• Mentor and develop data scientists through design reviews, technical guidance, and career coaching. 

• Influence technical direction across teams by driving alignment, knowledge sharing, and a culture of high-quality decision-making. 

WHO WE ARE LOOKING FOR 

• Advanced degree (MS or PhD) in a quantitative field such as Statistics, Computer Science, Economics, Applied Math, Operations Research, or similar. 

• 7+ years of experience working in a DS role that involves bringing products from ideation to production. 

• Deep expertise in statistical modeling, machine learning, and large-scale data analysis. 

• Strong understanding of experimentation, causal inference, and metric design in complex systems. 

• Familiarity with large-scale data and ML tooling (e.g. Spark, distributed training, real-time inference systems). 

• Proven ability to lead ambiguous, high-impact projects end-to-end as a senior individual contributor. 

• Excellent communication skills and the ability to influence across organizational boundaries. 

• Experience in programmatic advertising and/or real-time auctions is a plus. 

• Track record of mentoring senior data scientists and shaping team-level technical direction is a plus. 

Our work spans three interconnected areas: 

• Marketplace Execution: building the control systems, supply prediction models, and decisioning logic that enable buyers to execute their customized strategies efficiently and at scale.
• Marketplace Curation: developing recommendation systems and curation frameworks that help buyers construct customized inventory strategies balancing audience relevance, publisher quality, and scale.
• Inventory Science: designing the measurement frameworks and causal methods that quantify the impact of marketplace decisions on advertiser outcomes, and translate complex trade-offs into actionable insight. 

Responsibilities 

• Build and maintain control systems that dynamically allocate ad budgets across sell-side partners based on quality signals and performance targets. 
• Design and analyze experiments using causal inference methods to measure the impact of inventory decisions on advertiser KPIs, and develop the metrics that make those trade-offs visible and actionable. 
• Build the recommendation systems and curation frameworks that help buyers find supply that reaches their target audiences at scale and delivers on their campaign outcomes. 
• Develop time series models to anticipate supply volume shifts and help buyers and partners plan accordingly. 
• Partner with engineering, product, and business teams to translate research into scalable, production-ready systems that improve marketplace value for buyers and sellers.  
• Define the applied science roadmap for the team — identifying high-impact problems, scoping solutions end-to-end, and driving projects from research through production. 

Who You Are 

We're looking for a Staff Applied Scientist who thrives at the intersection of rigorous methodology and real-world systems. You are comfortable moving between statistical modeling, experiment design, and ML, and you know how to translate that work into scalable solutions that have a measurable impact on how billions of ad dollars are spent. You care about getting things right, and you're motivated by problems where the stakes are high and the data is complex. 

• Advanced degree in data science, statistics, machine learning, economics, applied math, computer science, or a related field
• 7+ years of experience in data science or 5+ years of experience with a PhD
• Experience of owning projects end-to-end (from research to productionization at scale)
• Strong grounding in machine learning, statistics, experimental design, causal inference, and metric development
• Experience with recommendation systems or ranking models
• Experience with large‑scale data processing (e.g., Spark, EMR, Databricks)
• Comfortable with practices that enable reproducible analyses and useful prototypes—clean code, version control, and code review 

Nice to Have 

• Experience in programmatic advertising, real-time auctions, or supply-side systems
• Familiarity with control theory, constrained optimization, or budget allocation systems
• Experience building or applying agentic AI workflows, including the use of LLMs for automation, decision support, or data-driven product features 

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.

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.

We are looking for a Senior Data Scientist to design, build, and scale data driven solutions powering our forecasting, pacing, and recommendation systems for our emerging channels. You will develop advanced machine learning or deep learning models that directly influence planning, allocation and performance on our platform.

The main job directions include:

• Develop forecasting models using statistical, ML and deep learning approaches.
• Build and optimize pacing algorithms that balance short-term performance with long-term objectives and constraints.
• Build custom solutions tailored to our unique environment, where off-the-shelf models often don’t scale effectively.
• Collaborate with product teams to understand business goals and translate them into actionable data science solution.
• Work closely with engineering teams to deploy models from prototype to production, ensuring smooth integration into products.
• Define success metrics, conduct offline evaluation and online experiments (A/B testing), and measure business impact.
• Communicate technical results and tradeoffs clearly to technical and non-technical audiences.

WHO WE ARE LOOKING FOR

- Proficient in open-source languages, you have a strong passion for enhancing and expanding your technical skills. Your expertise includes hands-on development of predictive models and solutions utilizing open-source tools and cloud computing platforms. Has a deep understanding of the foundations of statistics and machine learning

- Hands-on experience building data science solutions at scale. A track record of owning a project end-to-end (from research to production), and partnership with a cross-functional team of data scientists, engineers, and product managers to deliver the data science solution and models

WHAT YOU BRING TO THE TABLE

We 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 successful candidates typically come in with something like the following experience:

- BS/MS with 5+ years or a PhD with 3+ years of experience working in a DS and ML role that involves bringing products from ideation to production.

- Experience in building ML model in always-on production system and working with diverse technologies and data sources

- Strong experience in one or more of: forecasting, pacing systems, or recommendation systems.

- Proficient in Python

- Hands-on experience with deep learning frameworks (PyTorch, TensorFlow).

- Experience running heavy workloads on a distributed computing cluster (especially EMR or Databricks), leveraging technologies like Spark to work with large datasets.

- Experience in programmatic advertising and/or real-time auctions is preferred