Please consider donation to developer for continued support

RStudio creates great software that helps people understand data and make better decisions in real-world applications. Our core offering is an open-source data science toolchain, and we aim to make it available to everyone, regardless of their economic means. Our customers are leading-edge innovators in analytics, machine learning, big data, and similar domains and generally work in R and Python.
The Solutions Engineer is responsible for getting customers unblocked when installing, customizing and integrating RStudio Professional products into their on-premises and cloud environments. It is a highly technical role that works closely with our support, engineering and customer success teams. You will be responsible for ensuring that customers have a great experience using RStudio Professional products, through a combination of email, phone, and support ticket contact.
Because of your deep experience of Linux and Windows systems, cloud architectures (AWS, Azure and GCP), networking protocol, load balancing configurations, and authentication mechanisms, you can identify the root cause of installation problems effectively. You can then advise customers on the best solution, thus improving customer satisfaction and reducing time-to-value.
As a member of the solutions engineering team you will have the opportunity to grow and specialize your technical skills. You will work closely with the best engineers in the R and Python communities; you will help customer IT organizations solve complex problems; and you will help define best practices for using R and Python in production. Solutions engineers have a tremendous opportunity to grow their expertise and influence at RStudio. Some visible examples of the output of this team appears on solutions.rstudio.comdb.rstudio.com and docs.rstudio.com.
Responsibilities:
As a solutions engineer, you will spend the majority of your time directly helping customers to solve their challenges:
  • Install, configure and integrate RStudio products with customer systems. These installation service projects tend to be short, typically 2-3 days in duration.
  • Resolve escalated support tickets, by working directly with customers during support phone calls
  • Assist the customer success team with customer calls, where you will demo RStudio products, discuss technical architectures and answer general questions
  • Help build a knowledge base of support documents, customer demos, and marketing collateral
  • Technical representation of RStudio at trade shows (2-4 times per year)
  • Give presentations, training, webinars and workshops (e.g. at rstudio::conf)
You have:
  • Proven communication skills; specifically, the ability to explain complex problems to customers, with patience and empathy
  • desire for ongoing learning, keeping up-to-date with the latest cloud and data science technologies
  • Extensive experience working collaboratively with your team and across teams to solve challenging problems
  • A desire to share your knowledge, in the form of support articles, blog posts, training, etc.
You will be joining an extraordinary team that will value your contribution to expanding our capabilities as a team, so we are looking for expertise in several different areas. Although you may not have experience in all of these spheres, the ideal candidate will be exceptional in several of:
  • Linux system administration and integration
  • R and/or Python programming, with special emphasis on managing environments with virtualenv, venv, renv, packrat or similar
  • Authentication mechanisms, e.g. PAM, LDAP, SAML and are comfortable troubleshooting authentication integrations
  • Configuration of proxy servers and load balancers, e.g. Apache, NGINX, or cloud load balancers
  • Virtualization, e.g., Docker containerization, such that you are comfortable recreating test environments using Docker
  • Container orchestration, e.g., Kubernetes or Docker swarm
  • Managing RStudio professional products in production environments.
About us:
  • We welcome all talented colleagues and are committed to a culture that represents diversity in all its forms.
  • We prioritize giving ourselves “focus time” to get deep work done. We minimize meetings and aim to operate asynchronously.
  • We are a learning organization and take mentorship and career growth seriously. We hope to learn from you, and we anticipate that you will also deepen your skills, influence, and leadership as a result of working at RStudio.
  • We operate under a unique sustainable business model: over 50% of our engineering group is dedicated to creating free and open source software.  We are profitable and we plan to be around decades from now.
Notable:
  • 100% distributed team (or come in to one of our offices in Seattle or Boston) with minimal travel
  • Competitive compensation with great benefits including medical, dental, and vision insurance (100% of premiums covered)
  • 401k matching
  • A profit-sharing program when the company does well
  • A home office allowance or reimbursement for a coworking space
  • Flexible environment with a generous vacation policy
RStudio is committed to being a diverse and inclusive workplace. We encourage applicants of different backgrounds, cultures, genders, experiences, abilities, and perspectives to apply. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, sexual orientation, gender, gender identity, age, physical disability, or length of time spent unemployed.

from Jobs – Jobs for R-users https://ift.tt/2WavLuZ
via IFTTT

Introduction to R

R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.

R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity.

One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.

R is available as Free Software under the terms of the Free Software Foundation’s GNU General Public License in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.