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Blog - Jan Ahrend

Getting an User Experience Research Internship at Google

April 2017


There are two roles someone with a background in user research / HCI can take: One is the User Experience Researcher (UER) and the other one is the scientific researcher. The User Experience Researcher works closely with the product manager, engineers and designers on a particular product and helps to drive product design questions. The scientific researcher works on broader research questions that are often not specific to a product – their work often gets published. If you want to continue doing research similar to the projects you do at University, then scientific researcher may be best suited. If you want to work with real-world products and have direct impact on millions of users then User Experience Researcher may be best suited. All notes below are about the User Experience Researcher role but I would be happy to connect you with someone who just completed his DPhil and now works as a scientific researchers at Google.


Google’s HQ are in Mountain View (MTV) and most (interesting) work is done there. There are some other offices where User Experience Researchers work, including London. I recommend applying for a User Experience Researcher position in MTV. You can only apply in NA or Europe, not both. Once you started an application for one continent you can’t switch.


User Experience Research falls under “Engineering” (fields of work).User Experience Researchers  at Google are either qualitative or quantitative, or both. It’s okay to have a qual focus and not be strong in quant. Just make sure to point that out in your application and to your recruiter to manage expectations.


What kind of work you do in your internship depends on the team you are matched. I conducted eye-tracking studies, large-scale experiments, large-scale surveys, interviews and ethnographic field observations. I learned a lot in terms of methods and data analysis but also about effectively collaborating with stakeholders to operationalise research findings (something we academic researchers often have little experience in).


Some of the things that stood out to me during my User Experience Research internship in MTV was a culture where user research was understood to be crucial and highly appreciated (which is unfortunately often not common in other organisations or even Computer Science). There are hundreds of UERs working at Google and they have weekly/monthly/yearly meetups. The support for user research studies was outstanding. Google has dedicated teams that help with conducting studies (e.g. participant recruiting, legal aspects, etc.). This support goes so far that you can even have certain types of research studies completely conducted for you if you choose to. This frees up time for you to fully focus on designing studies and integrating research findings.


The infrastructure is also outstanding. Example; Google builds their own labs and fleet of user research vans all around the globe. And the financial support for studies is also fantastic. I got granted $1.000 for participant reimbursement within an hour, for example. This support is available to all UERs and interns. This lead to a role that could be described as ‘senior’ User Experience Researcher in other organisations – where you have teams working for you, to ‘enable’ your research. You can concentrate on the fun parts like designing studies, analysing and integrating findings.


The people are also genuinely nice and supportive – to a degree that I haven’t experienced in any other organisation.


One aspect that an academic researcher may be perceived as a drawback when working as a User Experience Researcher at Google is the product-centred nature of the work. While you still can publish papers, most of your work will be about improving the user experience of a product. If this is a strength or weakness will depend on your attitude/definition of ‘impact’.


To summarise, you will face a research environment that truly appreciates user research, uncomparable support in terms of infrastructure, finances and work force to conduct research studies, and interesting and motivated people.


How User Experience Research work differs from our academic work

As you may have sensed from the description above, the work focus shifts somewhat from analysing data to designing studies purposefully and feeding findings effectively back. Your main responsibility is not only to analyse data but to design studies appropriately so they will lead to impact on your product. You will need to collaborate closely with the product team and understand what research questions are most pressing, and then to communicate findings in a way that they will lead to actual impact. In our academic work, the analysis of data may be most ‘challenging’. The challenges I faced as a User Experience Researcher shifted more towards understanding what findings would be needed to drive pressing product decisions and how to effectively communicate them to product managers and engineers and work with designers to incorporate them into the product. It is not enough to have ‘interesting’ findings if they lead to no impact on the user experience.


UX and UX Research at Google



You will need a reference from someone working at Google otherwise your application will get lost. A reference will increase your chances of getting to the interview stage. You will need a tailored CV and motivational statement. A portfolio showcasing some of your work is not necessary but can help.


Interviewing tips

I am happy to answer any questions you may have!



Analysing the freelancing market (ODesk & Elance)


Hi all, I am Jan and I am passionate about human-computer interaction, product design and entrepreneurship. I am currently reading for my PhD in Computer Science at the University of Oxford, where I am researching (together with the MoD and Airbus) ways to improve the situational awareness of our nations’ cyber defenders by conceptualising the management of cyber threat intelligence and developing technologies that support their practices.

I used Kimono for my research, to efficiently put a database of cyber security companies together that I then used to reach out to selected organisations for a potential collaboration (it was very helpful). Right now, I am experimenting with ways to help me track and analyse the freelance market (Elance and ODesk) in regard to supply and demand. This has nothing to do with my research and is just out of curiosity. I am interested in the concept of productised services and explore the usefulness of transferring some of the concepts of keyword analysis (from SEO) to this domain.

But on a bigger picture, I want to explore the usefulness of web data extraction approaches that support day-to-day/operational and also strategic decision making in SMEs (small and medium-sized enterprises).
I would love to talk to anyone who has an opinion, experiences or ideas in this area.


So here is what I did:


1. Find the pages that output “all results”

For Elance, this is https://www.elance.com/r/jobs/sts-0
/sts-0 displays jobs with “any status” and doesn’t limit the results to jobs which “hiring (is) open”. If I would only scrape jobs that are open, I will miss a great deal of data, since we will scrape on an hourly basis and jobs are often allocated within minutes.

For ODesk, this is https://www.odesk.com/o/jobs/browse/st/-1/
The same holds for ODesk. /st/-1/ displays all jobs independent of their hiring status.


2. Configuring Kimono (the web scraping application)

Click on the fields that you want to collect and give them a variable name. Easy. See here for help how to use Kimono.


2. Scraping the base data set 

I want to scrape all displayed results once (these will be around 47.000 results for ODesk and 26.000 for Elance). This will give me the data set that I will add to with later scrapes and mirrors the current job openings on these platforms. Important here is to set the pagination correctly in Kimono (here for more information) and set “pagination limit” to “10000 pages max” under the “CRAWL SETUP” tab of both APIs. And I had the “AUTO-RUN FREQUENCY” on “manual crawl” – I only need the base set scraped once.

The first crawl may take a while to run through. I looked at the results of this scrape and made sure the outputs were as expected.


3. Setting up the auto-run feature to track new jobs

To determine the crawl frequency in regard to pagination limit, I went to the Elance and ODesk pages and checked several times a day through how many pages new job posting from within the last 60 would stretch. On Elance, job posting from the last 60 minutes will stretch through an average of 6 pages. On ODesk, this is 1 page.

I went back to the “CRAWL SETUP” and changed the “pagination limit” to “10 pages max” for Elance and “1 page max”.



Implications for design (Kimono)

  1. Ability to set a custom number for the pagination limit.
  2. Ability to add-to previous crawls when using the auto-run frequency.




Creating Design Briefs – Tool: CreateBrief

Create a free shareable design brief. No email needed.



Found on ProductHunt: https://www.producthunt.com/tech/create-brief

Try it yourself: http://www.createbrief.com/

The design brief created in this video: http://www.createbrief.com/brief/producthunt?id=1180

Startup co-founders

Finding a co-founder

What to look for in co-founders – Paul Graham on determination, flexibility, imagination, naughtiness and friendship

A guide to find the right co-founder – Co-founder relationships: from falling in love to outsourced tech and remote CTOs

Don’t “Look” for a Technical Co-Founder. Earn one with these steps – Too often do founders try to just “look” a co-founder, rather than “earn” one.

How to Find A Co-Founder For Your Startup – You can’t be great at everything. Finding your compliment could be what drives your company to success.

50 Ways to Find Co-Founders – Don’t know where to find a co-founder?

34 Questions to Ask Potential Co-Founders – Jessica Alter of Cofounder Dating outlines all of the questions you need to ask.

A Tech Founder’s Guide to Picking a Non-Tech Founder – Jessica Alter of Cofounder Dating shares a strong list of things to look for when finding a non-tech founder

How We Fight – Cofounders in Love and War – Steve Blank shares extremely important lessons on managing co-founders.


Places to find co-founders


Building a founding team
Where do you fit in? A Founder’s Guide to Startup Roles – Before you build a team, you should know your role in your company

Lessons about building a team from Zuckerberg and Facebook – This article explains how Mark Zuckerberg was able to build a great team from day one

How to Build Your Startup Team – This article explores the trenches of making your first hires

How to Assemble an All-Star Team for Your Startup – This video explains how to overcome the challenge of getting great talent to work for your young company

How to start a business with your significant other – Five tips to keep in mind: Set boundaries and expectations, Divide and conquer, Be your own person, Don’t lose your perspective, Always be honest, no exceptions


Steve Blank’s free online course on How to start a startup

Insightful startup podcasts

Fun fact: Most Founders of Technology Companies Graduated in Computer Science, 4x more than in Business or Economics

FormSwift’s Tax Guide for Freelancers and Businesses and Sample Business Plans



A hacker’s guide to finding startup jobs


Getting a job, no matter if internship or full-time, in Silicon Valley is a dream of many. And it is the many that can make it difficult to get a job. Afterall, the job market is a supply/demand market. The less demand a job offer has, the easier it can be to get the job.

There are a few dedicated startup job platforms:

http://venturefizz.com/jobs For boston and NY
AsiaWired.com – Looking for startups in Asia?  This may be the solution for you.
CoNotes.com – Focusing on nothing but jobs at startups, CoNotes has been around since 2007.
Dice.com – Browse jobs by city or pull up the category that applies to your skill set.
Jobs.Mashable.com – Our very own marketplace features categories for listing jobs and looking for them also.
NeoHire.com – Lets you look up jobs by category, add them to your basket as you find ones that interest you and then apply to all of the ones you’ve saved.
nPost.com – Besides offering numerous job listings at startups, they have 225+ interviews with people from some of the companies explaining what they are about and what they are looking for in an employee.
VentureLoop.com – Provides internship listings for students at certain schools and has job listings you can search by country or occupation.

While it is more convenient to simply go to Angel.co or StartUpHire and search through the database of job offers, there are many startups that don’t put their job openings on these platforms.


I will outline in the following an approach to find job applications that are likely to have less applicants – that are less advertised on job platforms.

We will circumvent the drawbacks of applying to jobs that are publicly advertised (e.g. on angel.co) by checking each Silicon Valley startup’s own job listings on their websites. But instead of doing this manually, we will automate most of the steps with the scraping tool KimonoLabs.


STEPS  Automatization Time needed
Step 1) Click through startup databases and find a company url automated
Step 2) Load the website, scan the website to find the page with job offers automated
Step 3) Analyse relevancy of job postings  automated
Step 4) If there are no job offers, search their email address for cold applications. automated For step 1-4: on average 30 seconds. For 1.000 startups that is 5.5 hrs



I am in my second year of my undergraduate studies and haven’t narrowed down my passion/career direction. I like many things, from product management, to marketing, to business development. Alternatively, in case you have a clear role you are looking for,

Step 1: Acquiring a dataset of companies

First, we will need to get a list of startups and their websites. We will use the databases of CrunchBase and Angel.co for this purpose.

To get a large data set of URLs of startups, we scrape a variety of sources.

Startup list curators: https://angel.co/companies?locations[]=Silicon+Valley&company_types[]=Startup

and https://www.funderbeam.com/startups?page=99999

We are adding an accelerator: 500startups: http://www.500.co/startup

And a VC firm: http://www.accel.com/#companies/2wire-acquired-by-pace

And a job search platform: https://www.google.co.uk/search?hl=en&q=site:http://www.ventureloop.com/ventureloop/companyprofile.php&gws_rd=cr&ei=1lY6Vfu4CorSaLL8gMgC&start=0&num=100


Note: The selection of sources is crucial for the usefulness of this whole process. Select the search parameters on each data source wisely (e.g. limiting to startups located in Sunnyvale). Of course, this is not just limited to startups. 

To scrape all these sources and export the URLs of our startups, we will use KimonoLabs. (a word on Kimono)

We now export all URLs and import them in Excel to combine them and get rid of duplicates and false websites. (Strip away “http://”, “www.” and “https:/” first and then get rid off obvious false positives such as *oracle.com/* and all URLs that link to sub-pages */*/. This is important and lead me to remove another 472 duplicates).


This leaves me with a final XXX startups that I have uploaded here – feel free to add new startups to the list!

Step 2: Scrape websites for relevant job offers

Key to this step Google’s search engine and an appropriate search query.

We will use the following search query to search each website for marketing internships, but experiment yourself with a few example companies to find the right search query:

site:*company_url*+marketing intern OR internship


Kimono scraping results:



It will not show job offers if the startup is exclusively using an outside provider to list the job offers (e.g. silkroad.com). Since we are looking for early stage (seed and series A, maybe B) startups, most will post their job offers on their website. Hence, this “limitation” may actually work in our favour. We won’t see job offers of any established big players.

Alternative A: Search for email for cold applications

site:*company_url*+jobs@*company_url* OR careers@*company_url* OR founders@*company_url*

Alternative B:




I took away two things from this weekend-project:

  1. Web scraping (i.e. the automation of intelligence gathering) is powerful for all sorts of decision making. Kimono was helpful.
  2. Google, and search filters on Google and the individual sources is powerful and essential to know how to use.


The bigger picture: using scraping to automate day-to-day decision making


I plan on writing a blog post about jobs that “allow remote”, “location independent”, “worldwide”.

Also, set up Google Alerts https://www.google.com/alerts