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Get Hired
Inside Scoop
  • They are known for their great culture, though there are some reports that it feels a little cult-like
  • Great perks like free food, gym, and opportunities for personal/professional growth
  • The compensation for these roles is at the very high end of the spectrum compared to similar companies.
  • Management is reviewed favorably in general.
 
Interview
Interview Process

The interview process for a software engineer at LinkedIn usually takes about 1-2 months.

Stage 1: HackerRank test (might be skipped)
Stage 2: Phone screen with recruiter
Stage 3: Technical phone interview with coding challenges via collabedit
The technical interview involves questions about general data structures and medium difficulty (Leetcode level) coding exercises via collabedit.
Stage 4: Onsite interview
The onsite interview consists of 5-6 rounds involving 1 hour sessions, of which 2 are coding sessions, 1 is a system design session, 1 is a technical communications session to explain past project(s), and 1 is a behavioral session.

The interview process for a data scientist can last anywhere between 3 weeks and 2 months.

Stage 1: Phone screen with recruiter
Stage 2: Technical phone interview
Questions are mostly about SQL, R, case study, and programming ability.
Stage 3: Onsite interview
The onsite interview lasts about 5 hours and usually consists of 4 rounds -- 2 coding (data structure and algorithms; 2 questions per round), 1 system design round, and 1 manager (behavioral) round. Questions are mostly focused on A/B, stats/probability, data analysis ability, and experience sharing.

The average interview process for a product/experience/UX UI designer at LinkedIn is about 4 weeks.

Stage 1: Phone screen with recruiter
Stage 2: Phone interviews (2)
These phone interviews are with a design manager and a senior designer
Stage 3: Design exercise, which will be presented at the onsite
Stage 4: Onsite interview
The onsite interview visit includes a 1 hour presentation about the candidate as a designer and a person, plus a presentation on their solution to the take-home design design homework - to an open/invitation interview panel (audience of 15-20 people). This is followed by questions. Next comes 4 1-on-1 interviews that are 45 min long with design managers from different teams.

The average timeframe of the interview process for a product manager is about 1 month.

Stage 1: Phone screen with recruiter
Stage 2: Technical phone interview with a product manager
Stage 3: Onsite interview
The onsite includes 3-4 45 minute interviews with team members, product manager(s), and any of the following: directors, 'engineering managers, and data science managers. Questions range from personality questions, situational questions, product sense questions, thoughts/impressions of the industry, as wells as direct questions related to specific issues LinkedIn is encountering.

 
Interview
Interview Questions
  • Union of two lists.
  • A string-type problem and a dynamic programming problem.
  • Write an algorithm to pick the top 3 largest numbers from a list.
  • Architect the LinkedIn home screen (feed) for the mobile app.
  • Implement a HashMap with primitives and find all the palindromic subsequences.
  • Find the number of possible permutations of paths given n number of stairs and 1, 2, or 3 stairs jump.
  • Given a string, return a boolean value for if it is a valid number
  • Given an array of numbers and a target value, return indices for numbers in the array which sum to this target value.
  • Tree traversal
  • Flowerbed problem.
  • Lowest common ancestor in binary tree
  • Given 2 nodes then asked 2 questions: 1. if the node class had a parent pointer 2. if the node class did not have a parent pointer.
  • How do you build a key value store?
  • What is the difference between thread and process?
  • What is the virtual memory?
  • Implement get() and put() methods from HashTable.
  • Recursion.
  • Implementation of a clustering algorithm.
  • K-means.
  • Implement a means for a collection of 2d points.
  • Shuffle an array.
  • Design the blacklist and implement hashmap
  • Trees, DP, Graphs.
  • What is event bubbling, get and post?
  • Code JavaScript palindrome algorithm, then optimize.
  • How many active members does LinkedIn have right now?
  • What is the business model at LinkedIn?
  • How would you design an A/B test for the homepage?
  • Given a random generator that produces a number 1 to 5 uniformly, write a function that produces a number from 1 to 7 uniformly
  • SQL, coding (R/Python), product case, machine learning, and stats.
  • What is the optimization problem for a SVM?
  • Describe a previous project.
  • How can you help to improve sales given a LinkedIn database?
  • What product metrics do you construct? How do you tell if your experiment is successful?
  • How many lines do you think a user's daily login table has?
  • SQL question about joining two tables with some conditions.
  • Come up with some of the factors that could be used to produce certain algorithms ('people you may know,' and an algorithm to discover when a person is starting to search for new job).
  • Basic data mining questions, including the concepts of classification and clustering
  • NLP questions, like named entity extraction,
  • Data mining questions, like SVM
  • Sampling question which is quite similar to Reservoir sampling.
  • Talk about a product that you want to build at LinkedIn
  • Generating a sorted vector from two sorted vectors.
  • Design recommendation engine for jobs.
  • How would you attract people who are not interested in LinkedIn to use the platform?
  • How would you design a 1000 story building so that people can efficiently get out of the building during rush hours (lunch hours)?
  • Tell me about your portfolio. Pick a project and walk me through your process.
  • What would be the next feature you would add if you had the time?
  • What feature or piece of work are you most proud of?
  • Tell me about a product that you think could be improved.
  • How would you increase enterprise engagement?
  • If you were a VC, are you more bullish on AR or VR? What app would you build? What would be your killer feature?
  • Describe how you would pitch to a Microsoft CEO that LinkedIn is a good acquisition.
  • A/B testing question - how would you test a certain LinkedIn feature? (Ex: 'people you may know' feature). How would you initially think about it when you don't have any data to base the decision off of?
  • What are your 2 main product management principles?
  • At what point is the product ready for production?
  • What is a LinkedIn feature that you love? Be prepared to talk at length about it. Be able to take it apart.
  • What are some main KPIs for project X? Be able to talk at length about metrics and KPIs.
  • What is a product you would improve? (Be ready to talk at length about why your improvement is important and how you could market it).
  • How would you get sales professionals to post more links on LinkedIn? What metrics would you look at?
  • How would you get people to update their LinkedIn profiles?
  • Tell me about an app that you have recently downloaded. How was their onboarding process?
  • Tell me about a product that you love. Why? How would you make it better?
  • If you were the CEO of Facebook, what top 3 things would you do for the company?
  • How would you improve the signing process of LinkedIn?
  • Case study on elevators in a building.
  • How would you determine the success of a specific feature?
  • What improvements would you make to the site?
 
Culture
About Linkedin

Mission

To connect the world's professionals to make them more productive and successful. When you join LinkedIn, you get access to people, jobs, news, updates, and insights that help you be great at what you do.

Vision

To create economic opportunity for every member of the global workforce.

  • Members first
  • Relationships matter
  • Be open, honest, and constructive
  • Demand excellence
  • Take intelligent risks
  • Act like an owner
 
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Compensation
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Team
Demographics
 
Locations
Office Locations
  • Sunnyvale: 1000 W Maude Ave
  • London: Guardian House 119 Farringdon Rd
 
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