Senior Analyst - Infrastructure
GitHub US, Remote Competitive Long term Senior
Remote OK
About GitHub

Who We Are:

GitHub is the best place to share code with friends, co-workers, classmates, and complete strangers. Over 27 million people use GitHub to build amazing things together across 79 million repositories. With the collaborative features of and GitHub Business, it has never been easier for individuals and teams to write faster, better code.

What We Value:

Collaboration: We believe the best work is done together. Empathy: We believe in putting people first. Quality: We believe in setting the standard for excellence. Positive Impact: We believe in making the world a better place through our work. Shipping: We believe in creating things for the people using them.

Why You Should Join:

At GitHub, we constantly strive to create an environment that allows our employees (Hubbers) to do the best work of their lives. We've designed one of the coolest workspaces in San Francisco (HQ), where over half of our Hubbers work, snack, and create daily. The other half of our Hubbers work remotely in 18 countries across the globe.

We are also committed to keeping Hubbers healthy, motivated, focused and creative. We've designed our top-notch benefits program with these goals in mind. In a nutshell, we've built a place where we truly love working, we think you will too.

GitHub is made up of people from a wide variety of backgrounds and lifestyles. We embrace diversity and invite applications from people of all walks of life. We don't discriminate against employees or applicants based on gender identity or expression, sexual orientation, race, religion, age, national origin, citizenship, disability, pregnancy status, veteran status, or any other differences. Also, if you have a disability, please let us know if there's any way we can make the interview process better for you; we're happy to accommodate!

Job Description

Github is looking for an Senior Analyst - Infrastructure to join the Platform Operations group. You will focus on the Infrastructure technology stack (first party and cloud), providing finance and engineering partners with deep analysis, and sound recommendations; helping to inform our broader infrastructure allocation and investment strategy. You’ll get to work with large, complex data sets and solve difficult, non-routine analysis problems, applying advanced statistical methods as needed. This is an individual contributor position with significant growth potential.


  • Generate strategic & focused infrastructure recommendations (e.g. cost-benefit, capacity forecasting, experiment analysis, business process improvements)
  • Identify gaps in business / user network understanding, and turn intutions into hypotheses for analysis - Identify cross-functional priority projects and champion solutions
  • Develop, introduce and manage processes required to effectively manage company’s current activities and operations as well as its plans for growth
  • Data-informed research and provider analysis
  • Comfortable delivering effective presentations of findings at multiple levels of stakeholders
  • Develop and automate reports, iteratively build and prototype dashboards to provide insights at scale, solving for analytical needs


Minimum Qualifications

  • 3+ years experience as a ‘full stack’ analyst / data scientist
  • Capable of statistical analysis, ad hoc etl, writing data pipelines
  • Experience articulating business questions and using mathematical techniques to arrive at an answer using available data.
  • Exposure to infrastructure-related problems around cost management, endurance, component availability, etc.
  • Experience translating analysis results into business recommendations.
  • Demonstrated leadership and self-direction.
  • Demonstrated willingness to both teach others and learn new techniques.
  • Demonstrated effective written and verbal communication skills.
  • SQL, Python, and R (or equivalent).

Preferred Qualifications

  • Masters in quantitative or strategic field
  • Experience deploying models to production environments
  • Experience as a topic/tech lead on an engineering (or other technical) team

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