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PhD Data Scientist, Intern
Оценка ИИИсключительная возможность для студентов PhD поработать в одной из самых престижных финтех-компаний мира. Программа предлагает реальные проекты, сильное менторство и конкурентную среду, что является идеальным стартом для карьеры в индустрии.
Сложность вакансии
Оценка ИИВысокая сложность обусловлена требованием статуса PhD в количественной области и необходимостью владения продвинутыми методами машинного обучения и причинно-следственного вывода. Отбор в Stripe традиционно очень строгий и включает проверку как технических навыков, так и умения решать бизнес-задачи.
Анализ зарплаты
Оценка ИИДля PhD-интернов в топовых технологических компаниях Торонто зарплата обычно значительно выше средней по рынку для обычных стажировок. Указанный диапазон отражает премиальный статус Stripe и высокие требования к кандидатам уровня PhD.
Сопроводительное письмо
I am writing to express my strong interest in the PhD Data Science Internship at Stripe in Toronto. As a PhD candidate in a quantitative field with a focus on advanced statistical modeling and machine learning, I have long admired Stripe’s data-driven approach to building financial infrastructure. My academic research involves handling complex datasets and applying rigorous analytical methodologies, which aligns perfectly with Stripe's mission to increase the GDP of the internet through actionable insights.
During my doctoral studies, I have developed extensive experience in Python and SQL, as well as a deep understanding of causal inference and experimentation. I am particularly drawn to this internship because of the opportunity to work on high-impact projects, such as optimizing charge flows or quantifying risk exposure, under the mentorship of industry experts. I am eager to bring my technical expertise and passion for solving large-scale problems to the Data Science team at Stripe and contribute to the team's roadmap for Summer 2026.
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Откликнитесь в stripe уже сейчас
Присоединяйтесь к Stripe, чтобы применить свои научные знания для масштабирования мировой интернет-экономики!
Описание вакансии
Who we are
About Stripe
Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.
About the team
Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We’re looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our work is broad and varied, influencing how our products work (e.g. understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background.
What you’ll do
About the internship experience
Our internship program provides the opportunity to work on meaningful business initiatives that will grow the GDP of the internet. Through the internship, you will work with many systems and technologies, gain experience in working with large datasets and analytical methodologies/tools to help us better understand our users and build better products.
Each intern has a dedicated mentor, and every intern project is part of the team's roadmap that will directly contribute to Stripe's mission. As you collaborate with industry experts on initiatives that expand global commerce, you will develop a strong first-hand understanding of the role analytics plays in steering business strategy and results.
We're not just focused on your immediate contributions; we're invested in your growth. Stripe sees this internship as an opportunity to grow your technical expertise and facilitate personal development, preparing you for a career in the tech industry.
Responsibilities
You will:
- Partner closely with Data Scientists, Data Analysts, and business partners to drive business impact through rigorous analytical solutions
- Apply machine learning, causal inference, or advanced analytics on large datasets to: i) measure results and outcomes, ii) identify causal impact and attribution, iii) predict the future performance of users or products, to drive business success
- Influence business actions and strategy by developing actionable insights through metrics and dashboards.
- Drive the collection of new data and the refinement of existing data sources.
- Learn quickly by asking great questions, finding how to work with your mentor and teammates effectively, and communicating the status of your work clearly
- Present your work to the Data Science team, partner teams, and fellow interns
Who you are
Minimum requirements
We’re looking for someone who has:
- Enrolled in a quantitative *PhD program* (e.g. Data Science, Statistics, Economics, Mathematics, etc.) with the expectation of graduating in winter 2026 or spring/summer 2027
- Experience with a scientific computing language (such as Python, R, etc) and SQL. We believe new programming languages can be learned if the fundamentals and general knowledge are present!
- Knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and/or experimentation
- Experience communicating and collaborating with multidisciplinary stakeholders in a team environment
Preferred qualifications
You also likely have:
- Experience writing and debugging data pipelines
- Demonstrated ability to evaluate and receive feedback from mentors, peers, and stakeholders via experience from previous internships or other multi-person projects
- Ability to learn new systems and form an understanding of those systems, through independent research and working with a mentor and subject matter experts
\\ This role is not eligible for hire in the United States - we are hiring only in Toronto, Ontario, Canada for summer 2026.
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Навыки
- Python
- Machine Learning
- SQL
- Statistics
- Data Pipelines
- Optimization
- R
- Product Analytics
- Causal Inference
- Experimentation
Возможные вопросы на собеседовании
Stripe активно использует эксперименты для оптимизации продуктов. Важно понимать, как кандидат справляется с внешними факторами.
Как бы вы спроектировали эксперимент для оценки влияния новой функции оплаты, если стандартное A/B тестирование невозможно из-за сетевых эффектов?
Для PhD интерна важно уметь применять сложные методы к реальным данным.
Расскажите о случае, когда вам пришлось использовать методы причинно-следственного вывода (causal inference) в вашем исследовании или проекте. Каковы были основные трудности?
Работа в Stripe требует не только построения моделей, но и понимания их влияния на бизнес.
Как бы вы оценили финансовый риск при запуске Stripe в новом регионе, используя имеющиеся транзакционные данные?
Проверка навыков работы с данными и понимания жизненного цикла разработки.
Опишите ваш опыт построения и отладки пайплайнов данных. С какими проблемами качества данных вы сталкивались чаще всего?
Интерны должны уметь объяснять сложные концепции коллегам из других отделов.
Как бы вы объяснили концепцию p-value или доверительного интервала менеджеру по продукту, не имеющему технического образования?
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