bobbyali/data_scientist_job_resources.txt

## data_scientist_job_resources.txt
This document contains a set of resources for helping to find a job in data science. It's possibly focused more on
getting an initial junior data scientist role, and a foothold into the industry. Give me a shout if you would like any
help with any of this.

CV PREP
=======

Here are some general tips for writing a decent CV:
http://www.base36.com/2013/03/10-tips-for-a-successful-technical-resume/

Do you have any projects that you can show on your CV? If you publish a project on Github, make sure you write a simple
and clear introduction README.md page, and maybe even consider putting together a 30-60 second video that summarises
the work. If you haven't got any projects, it could be worth having a go at one.


INTERVIEW PREP
==============

Here are personal/conversational questions you should prepare:

- What can you tell me about yourself?
- Can you list your strengths?
- What weaknesses do you have?
- Why should I consider hiring you?
- Where do you see yourself five years from now?
- Why do you want to work here?
- What is your salary expectation?
- What motivates you?
- What makes a good team player?
- Is there anything that you would like to ask me?

(see this link for top 50 interview questions)
https://www.forbes.com/sites/jacquelynsmith/2013/01/11/how-to-ace-the-50-most-common-interview-questions/#19754f954624


Here are technical questions you should prepare:

(see links below for suggestions)
http://www.kdnuggets.com/2016/02/21-data-science-interview-questions-answers.html
http://www.kdnuggets.com/2016/02/21-data-science-interview-questions-answers-part2.html
http://rpubs.com/JDAHAN/172473
https://www.quora.com/How-do-I-prepare-for-a-data-scientist-interview
https://www.quora.com/What-are-some-common-Machine-Learning-interview-questions
https://www.reddit.com/r/datascience/comments/52hklz/data_science_interview_questions/?st=it1a8fze&sh=1199171d

When you do an interview, write down all the technical questions immediately afterwards. Then prepare answers for them.
They'll eventually come up again and you'll be prepared next time!


Here are ideas for questions that you can ask the interviewer:

- What does success look like for this position? How will I know if I am accomplishing what is expected of me?
- What is the last project you shipped? What was the goal, how long did it take, what were the stumbling blocks, what tools
did you use, etc.
- What will my first 90 days in this role look like? First 180 days?
- Who will I report to and how many people report to that person? Do they have regular 1:1 with their team members?
Why did the last person who quit this team leave? The company?
- If a startup, how long is your runway? How are financial decisions made?
- What would be my first project here? Has someone already been working on this or is this in the aspirational stage?
- What is the current state of the data infrastructure? How much work needs to be done on getting the infrastructure and
pipeline into shape before we start analyzing that data?


PLACES TO FIND JOBS
===================

The PyData jobs email list (once a month) is a useful list of curated jobs:
http://ianozsvald.com/2016/01/12/data-scientist-jobs-in-london/
(here's the signup form: https://morconsulting.us5.list-manage.com/subscribe?u=833cadbc54533d1da7935054c&id=e8f9fe4f2b)

Hacker News has a monthly Who's Hiring thread (here's the one for Jan 2018):
https://news.ycombinator.com/item?id=16052538

They also have a Who Wants To Be Hired monthly thread:
(again Jan 2018) https://news.ycombinator.com/item?id=16052540

The PyData monthly London meetup often is a good place to hear about new jobs:
https://www.meetup.com/PyData-London-Meetup/

There are lots of London-based recruiters on my LinkedIn profile connections, and they'll be happy to talk to you if you reach out.
- On that note, it's worth having an up-to-date LinkedIn profile, since recruiters will be able to more easily find you this way. Also LinkedIn has a decent jobs section that could be worth looking into.

Shapr is a mobile networking app and sometimes you can find interesting people here who may be hiring for their companies.
	This document contains a set of resources for helping to find a job in data science. It's possibly focused more on
	getting an initial junior data scientist role, and a foothold into the industry. Give me a shout if you would like any
	help with any of this.

	CV PREP
	=======

	Here are some general tips for writing a decent CV:
	http://www.base36.com/2013/03/10-tips-for-a-successful-technical-resume/

	Do you have any projects that you can show on your CV? If you publish a project on Github, make sure you write a simple
	and clear introduction README.md page, and maybe even consider putting together a 30-60 second video that summarises
	the work. If you haven't got any projects, it could be worth having a go at one.


	INTERVIEW PREP
	==============

	Here are personal/conversational questions you should prepare:

	- What can you tell me about yourself?
	- Can you list your strengths?
	- What weaknesses do you have?
	- Why should I consider hiring you?
	- Where do you see yourself five years from now?
	- Why do you want to work here?
	- What is your salary expectation?
	- What motivates you?
	- What makes a good team player?
	- Is there anything that you would like to ask me?

	(see this link for top 50 interview questions)
	https://www.forbes.com/sites/jacquelynsmith/2013/01/11/how-to-ace-the-50-most-common-interview-questions/#19754f954624


	Here are technical questions you should prepare:

	(see links below for suggestions)
	http://www.kdnuggets.com/2016/02/21-data-science-interview-questions-answers.html
	http://www.kdnuggets.com/2016/02/21-data-science-interview-questions-answers-part2.html
	http://rpubs.com/JDAHAN/172473
	https://www.quora.com/How-do-I-prepare-for-a-data-scientist-interview
	https://www.quora.com/What-are-some-common-Machine-Learning-interview-questions
	https://www.reddit.com/r/datascience/comments/52hklz/data_science_interview_questions/?st=it1a8fze&sh=1199171d

	When you do an interview, write down all the technical questions immediately afterwards. Then prepare answers for them.
	They'll eventually come up again and you'll be prepared next time!


	Here are ideas for questions that you can ask the interviewer:

	- What does success look like for this position? How will I know if I am accomplishing what is expected of me?
	- What is the last project you shipped? What was the goal, how long did it take, what were the stumbling blocks, what tools
	did you use, etc.
	- What will my first 90 days in this role look like? First 180 days?
	- Who will I report to and how many people report to that person? Do they have regular 1:1 with their team members?
	Why did the last person who quit this team leave? The company?
	- If a startup, how long is your runway? How are financial decisions made?
	- What would be my first project here? Has someone already been working on this or is this in the aspirational stage?
	- What is the current state of the data infrastructure? How much work needs to be done on getting the infrastructure and
	pipeline into shape before we start analyzing that data?


	PLACES TO FIND JOBS
	===================

	The PyData jobs email list (once a month) is a useful list of curated jobs:
	http://ianozsvald.com/2016/01/12/data-scientist-jobs-in-london/
	(here's the signup form: https://morconsulting.us5.list-manage.com/subscribe?u=833cadbc54533d1da7935054c&id=e8f9fe4f2b)

	Hacker News has a monthly Who's Hiring thread (here's the one for Jan 2018):
	https://news.ycombinator.com/item?id=16052538

	They also have a Who Wants To Be Hired monthly thread:
	(again Jan 2018) https://news.ycombinator.com/item?id=16052540

	The PyData monthly London meetup often is a good place to hear about new jobs:
	https://www.meetup.com/PyData-London-Meetup/

	There are lots of London-based recruiters on my LinkedIn profile connections, and they'll be happy to talk to you if you reach out.
	- On that note, it's worth having an up-to-date LinkedIn profile, since recruiters will be able to more easily find you this way. Also LinkedIn has a decent jobs section that could be worth looking into.

	Shapr is a mobile networking app and sometimes you can find interesting people here who may be hiring for their companies.