ENH: (DS-702) Update DS applicant exam instruction + workflows to acc…

…ommodate applications for multiple roles!

README.md

@@ -11,10 +11,9 @@
 
 # Welcome!
 
-From all of us and Bombora Data Science, we're eager to get to know you! To do so, we'd thought we'd first engage you with a few exercises to demonstrate concepts we're interested and hope you are as well. 
+From all of us at Bombora Data Science, we're excited to get to know you! To do so, we'd like to begin by engaging in a few exercises exploring concepts we're interested in (and hope you are as well). 
 
-
-*Note*: We'll be leveraging open tools and public repositories. Ethics and professional aspirations should drive you to work creatively, enthusiastically, and *independently*. Clearly, you should leverage all resources you can, but please, *do not* share this exam or your solutions with anyone else. :)
+**NOTE**: We'll be leveraging open tools and public repositories. Ethics and professional aspirations should drive you to work creatively, enthusiastically, and *independently*. Clearly, you should leverage all resources you can, but please, *do not* share this exam or your solutions with any other entity, man or machine. :)
 
 Thank you so much! Now, get comfortable and let's go!
 
@@ -23,75 +22,97 @@ Thank you so much! Now, get comfortable and let's go!
 ## Overview
 We're going to leverage typical analysis and development workflows used by our team to conduct an interview exam. In short, you'll:
 
-- clone this repo, 
-- open the exam Jupyter notebook in an environment of your choice (web or local), 
-- select a language (kernel) of your choice (you can choose between Scala, R, Haskell, Python 2 or 3, Julia or even Bash), 
-- answer two questions of your choice,
-- add and commit your solution
-- add and commit your resume (and other docs, if you wish)
-- push your solution to your remote repo,
-- send us a PR with your completed exam submittal.
+- clone this repo and setup a working directory
+- open the exam Jupyter notebook in an [POSIX environment](https://en.wikipedia.org/wiki/POSIX) of your choice (web or local), using a language (kernel) of your choice (you can choose between Scala, R, Haskell, Ruby, Python 2/3, Julia or even Bash)
+- answer two questions of your choice
+- add, commit, and push your solution + resume (and other docs, if you wish) to your remote repo
+- send us completed exam submittal via a [pull request PR](https://help.github.com/articles/about-pull-requests/)
 
 ## Details
 
-### 1. Fork / clone this repo to your GitHub account.
+### 0. Configure exam params:
+Define a few parameters used throughout the exam:
+- `your-gh-username`: your [GitHub username](https://help.github.com/articles/remembering-your-github-username-or-email/).
+- `ds-position`: the title of the position you're applying to, specified in the email you recieved (e.g., `data-engineer-2017-q2`, `data-scientist-intern-2017-q3`)
+- `mylastname-myfirstname`: your name, backwards of course!
+
+If you're a POSIX shell user (e.g., linux or osx), you can set these params via environment variables so future commands won't have to be manually modified!
+
+```bash
+export GH_USERNAME='carlsagan'
+export DS_POSITION='data-science-director'
+export DS_EXAM_NAME='sagan-carl'
+```
+
+### 1. Make your own copy of repo
+
+#### Fork repo to your GitHub account
 
-#### Fork
 It's the button above that looks like the one below (you can click either):
 
 <!-- Place this tag where you want the button to render. -->
-<a class="github-button" href="https://github.com/bomboradata/datascience-exam/fork" data-icon="octicon-repo-forked" data-style="mega" data-count-href="/bomboradata/datascience-exam/network" data-count-api="/repos/bomboradata/datascience-exam#forks_count" data-count-aria-label="# forks on GitHub" aria-label="Fork bomboradata/datascience-exam on GitHub">Fork</a>
+<a class="github-button" href="https://github.com/bomboradata/datascience-exam/fork" data-style="mega" aria-label="Fork bomboradata/datascience-exam on GitHub">Fork</a>
 
 #### Local Clone
 
-On your local machine, with git installed:
+On your local machine, with `git` installed:
+```bash
+git clone git@github.com:$GH_USERNAME/datascience-exam.git
+cd datascience-exam
+```
 
-    git clone git@github.com:<your-gh-username>/datascience-exam.git
+#### Checkout `$DS_POSITION` branch
 
-#### Checkout `datascience-engineer-intern` branch
+Develop against a branch titled for the position you're applying to:
 
-Best if you develop against this branch:
-
-	git checkout datascience-engineer-intern
+```bash
+git checkout $DS_POSITION
+```
 
 
-### 2. Create your copy of `ds-interview-exam` nb
+### 2. Setup your exam working directory
 
-Create copy of `ds-interview-exam.ipynb` including your name, with the following command:
+1. Create your *exam directory*:
 
-	cp ds-interview-exam.ipynb submittals/data-engineer-intern/<mylastname-myfirstname>__ds-interview-exam.ipynb 
+    ```bash
+    mkdir ./submittals/$DS_POSITION/$DS_EXAM_NAME
+    ```
 
+2. Copy exam notebook (`ds-interview-exam.ipynb`) to your *exam directory*:
+
+    ```bash
+    cp ds-interview-exam.ipynb ./submittals/$DS_POSITION/$DS_EXAM_NAME/
+    ```
 
 ### 3. Setup Jupyter Notebook Environment
 
 #### 3.1 Launch Jupyter
 You have two options:
 
-1. **Upload the included `ds-interview-exam` notebook to [try.jupyter.com](try.jupyter.com)** (easy and recommended):
-	- open [try.jupyter.com](try.jupyter.com),
-	- Upload this notebook to 
+1. **Upload the included `ds-interview-exam` notebook to [try.jupyter.org](https://try.jupyter.org/)** (easy and recommended):
+	- open [try.jupyter.org](https://try.jupyter.org/),
+	- Upload this notebook to Jupyter session
 		- click `upload` in upper right corner
-   		- select the local notebook file (`data-science-exam.ipynb`)
+   		- select the local notebook file (e.g., your copy of `data-science-exam.ipynb`)
     - click on notebook to open.
 
-2. or, **create a local conda env**, if you prefer finer control of packages, (difficult):
+2. or, **create a local conda env**, if you prefer (much) more control of packages, (difficult):
     - [install conda / miniconda](http://conda.pydata.org/).
     - create `bombora-datascience-exam` conda environment, via (from repo root): 
         `conda env create -f bombora-datascience-exam.yml`
     - activate conda environment, via: 
         `source activate bombora-datascience-exam`
     - launch Jupyter, via: 
         `jupyter notebook`
-    - open `ds-interview-exam.ipynb` notebook 
+    - open your copy of `ds-interview-exam.ipynb` notebook 
 
 #### 3.2 Setup Jupyter
 
-**Note**: for those not familiar with Jupyter notebook, please view the *Welcome to ...* intro noteboooks included in file listing. Also, you can review the [Notebook Basics tutorial](http://nbviewer.jupyter.org/github/jupyter/notebook/blob/master/docs/source/examples/Notebook/Notebook%20Basics.ipynb).
+**Note**: for those not familiar with Jupyter notebook, please view the *Welcome to ...* intro notebooks included in file listing. Also, you can review the [Notebook Basics tutorial](http://nbviewer.jupyter.org/github/jupyter/notebook/blob/master/docs/source/examples/Notebook/Notebook%20Basics.ipynb).
 
 After opening your notebook, you'll need to select a language kernel of your choice, (you can choose between Scala, R, Haskell, Python 2 or 3, Julia or even Bash).
 
 - from menubar of the opened notebook, select * Kernel > Change Kernel > <your language>*
-
  
 
 ### 4. Solve TWO problems, one from each section.
@@ -100,24 +121,36 @@ After opening your notebook, you'll need to select a language kernel of your cho
 	- *1. Algo + Data Structures*
 	- *2. Prob + Stats*
 
-2. Take 10-15 minutes to review questions across each section.
+2. Take 10 minutes to review questions across each section.
 
 3. Select and answer **ONE** question from **EACH** section, or to be totally explicit:
 	- select and answer a question from section 1 (e.g., either Q1.1 or Q1.2).
 	- select and answer a question from section 2 (e.g., either Q2.1, Q2.2, Q2.3, Q2.4, or Q2.5).
 
-This is you, shining. Think, Hack, Repeat. Enjoy this part. :)
+This is you, _shining_. Think, Hack, Solve, Repeat. Enjoy this part. :)
 
 
 ### 5. Commit results and push to your remote repo.
-
-- add and commit solution notebook.
-- add and commit your resume with filename `mylastname-myfirstname__resume.myformat`
+ 
+- copy your resume (and additional docs) to your exam directory:
+    ```bash
+    cp path/to/my-resume.pdf ./submittals/$DS_POSITION/$DS_EXAM_NAME/
+    # (optional)
+    cp path/to/my-other-docs.pdf  ./submittals/$DS_POSITION/$DS_EXAM_NAME/
+    ```
+- add your *exam directory* and commit
+    ```bash
+    git add ./submittals/$DS_POSITION/$DS_EXAM_NAME
+    git commit -m "Exam submittal for $DS_POSITION"
+    ```
 - push to remote repo
+    ```bash
+    git push origin $DS_POSITION
+    ```
 
 ### 6. Open Pull Request to submit exam
 
-To submit, [please open a PR](https://help.github.com/articles/creating-a-pull-request/) to the `datascience-engineer-intern` branch of the repo.
+To submit, [please open a PR](https://help.github.com/articles/creating-a-pull-request/) to the `$DS_POSITION` branch of the repo.
 
 
 ## Questions?
@@ -130,9 +163,7 @@ Open an issue in the GH repo, we provide a button right here, for your convenien
 
 ## Finished, what's next? 
 
-Thank you for all of your hard work and your interest! You'll hear back from us, soon. :)
-
-Go enjoy your day, you deserve it!
+Go enjoy your day—you deserve it!
 
 
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bombora-datascience-exam.yml

@@ -1,10 +1,10 @@
-# A conda env supporting Bombora Data Science team interviews.
+# A conda env supporting Bombora Data Science application exams!
 name: bombora-datascience-exam
 # channels:
 #   - pandas
 dependencies:
   # core dependencies (must be installed)
-  - python>=3.5
+  - python==3.5.3
   - pip
   - psutil
   - pyyaml