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    Staff Data Analyst, Growth - Remote, United States - Stripe

    Stripe
    Stripe Remote, United States

    4 weeks ago

    Default job background
    Full time
    Description
    Who we areAbout 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 GTM (Go-To-Market) Analytics team is on the mission to maximize revenue by providing actionable insights and reporting to our partners across Sales, Marketing, and Growth. GTM Analytics is situated within the broader Data Science organization at Stripe, which is home to a diverse team of data analysts and scientists, product managers, and engineers that span their focus across sales, marketing, and product-led growth. GTM Analytics leverages sales, marketing, and product data to build and provide a wide variety of tools that are utilized across the company to drive business decisions.

    What you'll do

    As a senior member of the GTM Analytics team, you will lead analytical projects that shed light on our self-service business. You will increase our understanding of growth drivers and influence business outcomes by recommending solutions rooted in analyses and your deep understanding of Stripe's users. You will partner closely with cross-functional Growth pods of product managers, marketers, engineers, and data analysts and scientists that obsess over the experience Stripe users have on their journey to become customers – from initial signup through onboarding and retention.

    Responsibilities

    • Collaborate with Growth stakeholders to ideate, scope, and develop data products that shed light on Stripe's self-service business.
    • Influence Stripe's Growth roadmap by proactively identifying opportunities and emerging trends in Stripe's Growth business in ongoing forums.
    • Develop frameworks that allow for analysis at scale across Stripe's self-service experience.
    • Build and maintain data pipelines and dashboards that provide consistent and timely data and insights.
    • Work with finance partners on forecasting and planning models that provide visibility into the future of Stripe's self-service business.
    • Define key Growth metrics, gain consensus around their definitions, and drive adoption of their usage.

    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

    • 8+ years of experience in analytical roles working with large datasets
    • Bachelor's degree in Statistics, Economics, Mathematics, Engineering, Sciences or a related quantitative field
    • Proficiency in SQL and Python
    • Experience building self-serve dashboards or other scalable analytical tools for partner teams
    • Strong knowledge of statistics
    • Expertise in data storytelling and visualization, using data-driven insights to deliver actionable recommendations and drive business goals
    • Demonstrated ability to lead and deliver on multiple projects with a high attention to detail
    • Outstanding written and verbal communication skills

    Preferred qualifications

    • Master's degree in Statistics, Economics, Mathematics, Engineering, Sciences or a related quantitative field and/or experience in working on data analytics in the tech field
    • Experience developing data-informed narratives and visualizations for external publication
    • Experience working with institutions that are respected by policymakers and the wider public for their economic insight
    • Experience building and maintaining data pipelines using a distributed data framework (e.g. Hadoop, Spark)
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