Data Analyst, GTM Metrics & Reporting – Stripe

Full time @Stripe Career in Finance & Accounting
  • Illinois, United States, Chicago, Illinois, United States View on Map
  • Post Date : January 31, 2022
  • Apply Before : May 1, 2022
  • View(s) 53
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Job Detail

  • Job ID 41990
  • Career Level Mid-Senior
  • Gender All
  • Qualifications certificate
  • Language Requirement
  • Region North America
  • Other Classifications startup
  • Special Programs y-combinator
  • Remote No
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Job Description

Stripe exists to expand internet commerce and allow greater access to the online economy. We believe that talent is distributed equally but opportunity is not, and we aim to break down barriers to access by making it easy for new businesses and nonprofits to get started and equipping them with the tools they need to grow.
We’re looking for data analysts who are passionate about applying their analytical and engineering skills to democratize data, metrics and insights driven decision making for all Stripes. If you are naturally data curious, excited about deriving insights from data, experienced in improving availability and usability of those insights, and motivated by having impact on the business, we want to hear from you.
At Stripe, you’ll be part of a rich Data Science community for Analysts, Scientists and Engineers to learn and grow together. At the same time, our embedded org structure means that you’ll be working closely with our Sales and Marketing partner teams. You will:

Work closely with the Sales and Marketing partner teams to solve complex challenges at the intersection of business and technology using data.
Be the subject matter expert for data management including data integrity, acquisition, mining, analysis, forecasting, metrics and reporting.
Design, build and maintain business intelligence infrastructure to improve availability and usability of data and insights.
Drive strategic initiatives to improve the quality and timeliness of insights.
Build scalable automation solutions utilizing SQL, Presto, Spark, Tableau and other tools.
Provide operational support for initiatives across a range of technical and non-technical topics. 
Create analyses that tell a €œstory€ focused on business insights, not just data.
Apply models on large datasets to measure results and outcomes.
Partner with leaders effectively employing clear and structured communication.

We’re looking for someone with:

6+ Years of experience in a Business Intelligence Engineering, Data Engineering, Data Analyst and/or Data Science role, with a focus on building data pipelines and/or analyzing large data sets to solve problems.
Bachelor’s degree in Mathematics, Statistics, Engineering, or a related technical field.
Expert knowledge of SQL. 
Prior experience with writing and debugging data pipelines using a distributed data framework (Hadoop/Spark/Pig/etc.)
Prior experience with visualization using Tableau.
Strong knowledge of statistics and experimental design.
Entrepreneurial spirit that thrives in a fast paced environment, deals well with ambiguity and focuses on driving impact.
Proven ability to work cross-functionally, building and maintaining trust with internal stakeholders.
High attention to detail including precise and effective communications.
Hyper focus on and intuition for understanding the underlying needs of the business.
Impeccable product taste and demonstrated success shipping products with great user experiences at scale.

Nice to haves:

Master’s degree in Mathematics, Statistics, Engineering, or a related technical field.
Experience in AWS, GCP or Azure.
Knowledge of a scientific computing language (such as R or Python).
Prior experience at a growth stage internet or software company.
Good understanding of the development process and best practices (e.g. sprint planning, coding standards, code reviews, testing and validation) with an appreciation for maintaining a high quality bar with low operational overhead.

You should include these in your application:

Resume and LinkedIn profile.
Description of the most interesting analysis you’ve done, key findings and impact.
Link to or attachment of code you’ve written related to data analysis.
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