Data Scientist

United States·Seattlemid

Data ScienceData ScientistDataData & AI

2 views0 saves0 applied

Apply Now

Quick Summary

Key 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.

Requirements Summary

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.

Technical Tools

pythonsqletlforecastingmachine-learning

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.

Responsibilities

~1 min read

→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.

Requirements

~1 min read

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; and
2 years of experience applying statistical and machine learning models on large datasets to predict future performance of users or products.