Data Scientist
- Your hands-on, practical approach is excellent for building and debugging ETL pipelines and productionizing machine learning models.
- You are a natural problem-solver who enjoys tackling concrete, technical challenges like forecasting and experiment design.
- Your flexibility allows you to adapt to changing requirements and learn new tools quickly, which is valuable in a dynamic environment.
- You may find the extensive collaboration with Sales and business teams tedious, preferring to work independently on technical problems.
- Your tendency to avoid long-term planning could hinder the design of scalable, long-lasting data science solutions.
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.
What you’ll do
Responsibilities
- Apply statistical, time series forecasting and machine learning models on large datasets to predict future performance of users or products
- Partner closely with Sales and Data Science teams to identify important questions and answer them with data
- Design, implement and launch data science solutions using Python and R to empower data-driven decisions and products at scale
- Create analyses that generate insights for business teams
- Design, analyze, and interpret the results of experiments
- Build ETL data transformation pipelines in SQL
Who you are
Minimum requirements
Must have a Master's degree or foreign equivalent in Computer Science, Business Analytics, Statistics, or a related quantitative field, plus 3 years of experience in a Data Scientist or related occupation.
- 3 years of experience building ETL data transformation pipelines in SQL
- 3 years of experience working closely with product and business teams to identify important questions and answer them with data
- 2 years of experience productionalizing and implementing machine learning models
- 2 years of experience productionalizing and implementing software products
- 2 years of experience designing, analyzing, and interpreting the results of experiments
- 2 years of experience designing, and analyzing software architectures
- 2 years of experience designing, implementing, and launching data science solutions
- 2 years of experience designing, implementing, and launching software solutions
- 2 years of experience applying statistical and machine learning models on large datasets to predict future performance of users or products
Salary : $192,000 - $288,000/yr.
This salary range represents the base salary range for the role and any sales commissions/sales bonuses targets, if applicable, would be in addition to the base salary.
40 hrs/week
50% Telecommuting Permitted.
Multiple Positions Available.
Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends. WA04 #LI-D
LINI
Best personality fits for this role
Your strategic mindset and love for complex problem-solving align perfectly with applying statistical and machine learning models to predict future performance.
Read the INTJ career guide →Your leadership drive and strategic outlook are perfect for identifying key business questions and driving data-informed decisions.
Read the ENTJ career guide →Your natural curiosity and love for abstract models make you excellent at exploring new statistical and machine learning techniques on large datasets.
Read the INTP career guide →