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Software Engineer, Data Science Infrastructure
Entertainment & Media Industry Company
San Francisco, CA, United States
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Why is Data Science Infrastructure important at Company?
We develop tools that help every employee at Company make data-driven decisions. Every team at Company—product, operations, customer support, and leadership—relies on the data we collect about user behaviors and needs to make impactful decisions. Our toolchain democratizes access to data for everyone and makes it easy and painless to run A/B tests to establish cause and effect.
Our work is high-leverage: it makes the entire company, particularly the product organization, able to iterate faster and make changes that accelerate business growth. You will have visibility into every other team. Great candidates thrive at the intersection of Software Engineering and Data Science and are motivated to help Data Scientists, Product Managers, and Software Engineers make data-driven decisions.
What are examples of work that Data Science Infrastructure Engineers have done at Company?
Experiment Reporting Framework: Our homegrown A/B testing platform, which automates experiment setup, assignment, and analysis, and displays experiment results in a way that makes decision-making easy and fast. A/B testing is the building block of decision-making on Company's product team.
Blog post: Company website-reporting-framework/
Airpal: A query authoring interface that provides access to our data warehouse to everyone in the company. Eliminating barriers to our datasets allows every team to understand their relationship to Company and its users. We open-sourced Airpal in 2015.
Blog post: Company website/
The following experience is relevant to us:
• Building A/B testing tools that allow engineers and product managers to deploy experiments and analyze their results
• Making interactive interfaces for exploration of session activity
• Building novel visualization tools that help employees easily use core datasets to generate insights
• Leveraging data infrastructure and distributed systems to answer questions
• Identifying internal information needs and addressing them by creating novel tools
• Working with data at scale, specifically with distributed systems
• Strong scripting ability
• Background in Computer Science, Statistics, Applied Math or other quantitative related field is preferred
• Full-stack/generalist webapp development experience preferred
Benefits:
• Stock
• Competitive salaries
• $2000 yearly employee travel coupon
• Paid time off
• Medical, dental, & vision insurance
• Life insurance and disability benefits
• 401K
• Flexible Spending Accounts
• Apple equipment
• Company sponsored tech talks
• Breakfast, lunch, and dinner
• Weekly happy hour