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Every open role from the boards that matter, in one pool you can search, score against your CV and track.

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The pool

Every open role, one list

4,480 live roles read straight from 4 job boards. 2,030 of them are remote.

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Software1,546Data & AI445Design71Product166Sales722Marketing170Support145Operations317Finance127People65Legal87Other619
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Greenhouse3,284Ashby1,167Lever25Glints4

590 roles

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  • S

    Data Scientist

    3y ago

    Stripe · Toronto

    Mid

    Machine Learning · Cross-functional Collaboration · A/B Testing · Performance Optimization · Financial Modeling +5

    Greenhouse· Last observed unknown· Open status unconfirmed

  • P

    Sr. Data Scientist, Monetization

3y ago

Pinterest · San Francisco, CA, US; Seattle, WA, US

Senior

A/B Testing · Python · SQL

Greenhouse· Last observed unknown· Open status unconfirmed

  • P

    Sr. Machine Learning Engineer, Core Engineering

    3y ago

    Pinterest · Toronto, ON, CA

    Senior

    NLP · Recommender Systems · Machine Learning · A/B Testing · Deep Learning +4

    Greenhouse· Last observed unknown· Open status unconfirmed

  • S

    Data Scientist

    3y ago

    Stripe · N/A

    Mid

    Machine Learning · Cross-functional Collaboration · A/B Testing · Performance Optimization · Financial Modeling +5

    Greenhouse· Last observed unknown· Open status unconfirmed

  • S

    Data Analyst

    3y ago

    Stripe · US

    Mid

    Business Intelligence · Cross-functional Collaboration · ETL · Code Review · Analytics +3

    Greenhouse· Last observed unknown· Open status unconfirmed

  • D

    Staff Data Scientist - Infrastructure

    3y ago

    Databricks · Mountain View, California

    Lead

    Machine Learning · Spark · Code Review · Databricks · Data Warehousing +4

    Greenhouse· Last observed unknown· Open status unconfirmed

  • D

    PhD GenAI Research Scientist Intern

    3y ago

    Databricks · San Francisco, California

    Intern

    Deep Learning · Databricks · Data Warehousing · Analytics · PyTorch +2

    Greenhouse· Last observed unknown· Open status unconfirmed

  • S

    Data Analyst

    3y ago

    Stripe · Canada

    Mid

    Business Intelligence · Cross-functional Collaboration · ETL · Code Review · Analytics +3

    Greenhouse· Last observed unknown· Open status unconfirmed

  • O

    Data Engineer

    3y ago

    OpenAI · San Francisco

    RemoteRemote country eligibility unknownMid235k–385k

    ETL · Data Warehousing · Airflow · Python · Hadoop +4

    Ashby· Last observed unknown· Open status unconfirmed

  • D

    Staff Data Scientist

    5y ago

    Databricks · San Francisco, California

    Lead

    Recommender Systems · Product Management · Machine Learning · Customer Success · Spark +9

    Greenhouse· Last observed unknown· Open status unconfirmed

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    Greenhouse

    Data Scientist

    Stripe · Toronto

    Apply on GreenhouseOpen full page
    Level
    Mid
    Where
    Toronto
    Posted
    3y ago
    Last seen on its board
    Unknown

    Skills in this posting

    • Machine Learning
    • Cross-functional Collaboration
    • A/B Testing
    • Performance Optimization
    • Financial Modeling
    • Analytics
    • Python
    • Hadoop
    • Spark
    • SQL

    The posting

    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, and 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 We're looking for a variety of Data Scientists to partner with the Product, Finance, Payments, Security, Risk, Growth, and Go-to-Market teams. You'll work closely with a specific part of the business, playing a crucial role in optimizing our systems and leveraging data to make strategic business decisions. As Data Scientists at Stripe, it's our mission to ensure that the company strategy, products, and user interactions make smart use of our rich data, using techniques like machine learning, statistical modeling, causal inference, optimization, experimentation, and all forms of analytics. Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. Minimum requirements - PhD with 3+ years, MS or MA with 6+ years, or BS or BA with 8+ years of data science or quantitative modeling experience - Proficiency in SQL and a computing language such as Python or R - Experience in working with cross-functional teams to deliver results - Ability to communicate results clearly and a focus on driving impact - A demonstrated ability to manage and deliver on multiple projects with a high attention to detail - Strong business acumen and experience in synthesizing complex analyses into actionable recommendations - Proficiency with AI tools to accelerate model development, analysis, and coding Preferred qualifications - Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and experimentation - Experience deploying models in production and adjusting model thresholds to improve performance - Experience designing, running, and analyzing complex experiments or leveraging causal inference designs - A builder's mindset with a willingness to question assumptions and conventional wisdom - Experience with distributed tools such as Spark, Hadoop, etc. - A PhD or MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)

    Open the full page to draft a cover letter, research the company and track your application.