Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Data Science @ 4
Experimentation
Marketing
Mathematics @ 6
Payments
Python @ 4
SQL @ 4
Statistics @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Stripe, LLC. 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. Stripe’s mission is to increase the GDP of the internet.
Responsibilities
- Build statistical models, define and analyze product and operational metrics, explore experimental design, and construct exploratory analyses with internal data.
- Work closely with product and business teams to identify important questions and answer them with data.
- Collaborate with other data scientists, engineers, and operations teams to formulate innovative solutions for experimentation and implement advanced data-mining techniques.
- Conduct exploratory analyses on internal data to understand user behavior and inform product development.
- Drive the collection of new data and the refinement of existing data sources.
- Apply statistical and machine-learning models to large datasets to measure results and outcomes, and identify causal impact and attribution.
- Predict future performance of users or products.
- Define, measure, and monitor key outcome metrics for teams and support Stripe’s business.
- Communicate complex concepts and the results of metrics and analyses clearly and effectively through creative visualization.
- Communicate findings broadly and interact with teams including product managers, software engineers, marketing, and business development.
Requirements
- Master’s degree or foreign equivalent in Operations Research, Statistics, Industrial Engineering, Business Analytics, Mathematics, or a related field.
- At least three years of experience in Data Science or a related occupation.
- At least three years of experience with statistical and machine-learning methods, numerical optimization and integer programming, SQL, Python, optimization, and forecasting and machine-learning domains.
Additional Details
- Salary: $192,000–$288,000 per year.
- 40 hours per week.
- 50% telecommuting permitted.
- Up to 10% domestic travel required.
- Multiple positions available.
Benefits
Benefits may include equity, company bonus or sales commissions/bonuses, a 401(k) plan, medical, dental, and vision benefits, and wellness stipends.
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