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- США
- Зарплата
- 124 900 $ – 228 900 $
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Senior Applied Scientist , Channel Growth
Отличная вакансия в топовой AdTech компании с прозрачным диапазоном зарплаты и сильным соцпакетом (акции, страховка, 401k). Роль предполагает высокую степень ответственности и работу с передовым стеком технологий, что гарантирует профессиональный рост.
Сложность вакансии
Высокая сложность обусловлена требованием опыта (5+ лет) и необходимостью владения полным циклом разработки: от математических исследований до вывода моделей в продакшн (MLOps). Работа в сфере AdTech требует понимания специфики аукционов в реальном времени и обработки огромных массивов данных.
Анализ зарплаты
Предложенный диапазон ($125k – $229k) полностью соответствует рыночным стандартам для Senior Applied Scientist в технологических хабах США, таких как Сан-Хосе и Белвью. Верхняя граница диапазона даже несколько превышает медиану, особенно с учетом бонусов и акций.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Applied Scientist position at The Trade Desk. With over five years of experience in developing and productionizing machine learning models, I have a proven track record of building end-to-end solutions that drive business impact. My background in forecasting and pacing systems, combined with my proficiency in Python, PyTorch, and Spark, aligns perfectly with the requirements for scaling data-driven solutions for your emerging channels.
In my previous roles, I have successfully led projects from the ideation phase through to full-scale production, working closely with cross-functional teams of engineers and product managers. I am particularly drawn to The Trade Desk's culture of end-to-end ownership and the challenge of building custom solutions where off-the-shelf models fall short. I am confident that my technical expertise in deep learning and distributed computing will allow me to contribute significantly to your recommendation and allocation systems.
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Откликнитесь в thetradedesk уже сейчас
Присоединяйтесь к The Trade Desk, чтобы создавать передовые ML-решения для глобальной рекламной платформы!
Описание вакансии
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 ourforecasting, 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 algorithmsthat 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
CO, CA, IL, NY, WA, and Washington DC residents only: In accordance with CO, CA, IL, NY, WA, and Washington DC law, the range provided is The Trade Desk's reasonable estimate of the base compensation for this role. The actual amount may differ based on non-discriminatory factors such as experience, knowledge, skills, abilities, and location. All employees may be eligible to become The Trade Desk shareholders through eligibility for stock-based compensation grants, which are awarded to employees based on company and individual performance. The Trade Desk also offers other compensation depending on the role such as variable compensation-based incentives and commissions. Plus, expected benefits for this role include comprehensive healthcare (medical, dental, and vision) with premiums paid in full for employees and dependents, retirement benefits such as a 401k plan and company match, short and long-term disability coverage, basic life insurance, well-being benefits, reimbursement for certain tuition expenses, parental leave, sick time of 1 hour per 30 hours worked, vacation time for full-time employees up to 120 hours thru the first year and 160 hours thereafter, and around 13 paid holidays per year. Employees can also purchase The Trade Desk stock at a discount through The Trade Desk’s Employee Stock Purchase Plan.
The Trade Desk also offers a competitive benefits package. Click here to learn more.
Note: Interns are not eligible for variable incentive awards such as stock-based compensation, retirement plan, vacation, tuition reimbursement or parental leave
At the Trade Desk, Base Salary is one part of our competitive total compensation and benefits package and is determined using a salary range. The base salary range for this role is
$124,900—$228,900 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 accommodations@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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Навыки
- A/B Testing
- Python
- PyTorch
- Machine Learning
- Statistics
- Deep Learning
- Forecasting
- Apache Spark
- Databricks
- TensorFlow
- Amazon EMR
- Distributed Computing
Возможные вопросы на собеседовании
Позиция требует разработки кастомных решений для прогнозирования и аллокации ресурсов.
Расскажите о самом сложном проекте по прогнозированию временных рядов, который вы довели до продакшна: с какими проблемами масштабируемости вы столкнулись?
Вакансия подразумевает работу с распределенными системами.
Как вы оптимизируете обучение моделей глубокого обучения (PyTorch/TensorFlow) при работе с терабайтными данными в Spark/Databricks?
В описании указано, что DS в компании являются 'end-to-end owners'.
Опишите ваш опыт настройки CI/CD пайплайнов и мониторинга качества моделей после их деплоя в высоконагруженную среду.
Упоминается важность A/B тестирования.
Как вы подходите к дизайну экспериментов в условиях, когда стандартное A/B тестирование затруднено из-за сетевых эффектов или аукционной механики?
AdTech — специфическая область.
Как бы вы спроектировали алгоритм темпа (pacing algorithm), который должен равномерно тратить бюджет клиента, максимизируя при этом KPI в условиях волатильного рынка?
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- Страна
- США
- Зарплата
- 124 900 $ – 228 900 $