1.Notification的CTR下降原因分析
2.如何测试notification的改动
3.如何推荐hashtag
4.Identify best friends on FB
5.如何判断qualification质量
6.CTR下降原因排查
7.计算response rate
8.计算过去7日发起至少3次Call的用户数
9.Binomial Experiment计算
10.计算硬币正面朝上的概率
11.如何判断group call的人数限制
12.Facebook story不如Ins story该怎么办
13.You are the PM for Facebook Sports
14.what metric would you set as North Star
15.Design a feature for meaningful connections for Groups
16. validate the idea
17. get into the business of food delivery
18.Build a product for kids for FB (
19.Build a food delivery service for Businesses
20.Define goals for Facebook Rooms?
21.design a feature for Facebook Portal
22.Design a new Job product for facebook?
23.make Apple safer for its users
24.blood and organ donation
25.Design a product to help people travel together
26.build a travel product
27. a PM at FB
28.help people find a dogwalker
29.Design a product for volunteering for Meta
30.Design Travel product for Instagram
31. favorite product or app
32.You are a PM at Meta
33.a Facebook PM
34.Design a product to buy and sell antique products on FB
35.improving the SFO airport experience
36.Design a product for roadtrips
37.How would you improve it
38.Design an app for parking as a start up
39.Design a product for travel.
40. A/B Test
41.a new podcasting feature for FB
42.Design a product to find doctor in the pandemic
43.a Facebook product for Christmas
44.Build a product for hybrid work
45.Why and what should FB build
46.How would you build a product for finding a new doctor
47.How would you encourage volunteering on FB
48.build a tool to encourage volunteering
49.make Instagram great for SMB segment
50.a product to help a user find rental housing
51.Design a product to learn musical instruments
52.Design a product in Fashion space for Facebook
53.Design an product in travel space for Instagram
54.building a product to help people learn languages
55.Create a product to teach cooking remotely
56.Build a product for real estate
57.What are the goals for FB Pay?
58.Design a product to help users find a handyman
59.what goals would you set
60.Set goals for Facebook Live
61.Design a product for health
62.Design a product to learn Japanese
63.Design a sport related product for Facebook
64.define the goals
65.How would you build a grocery shopping experience?
66.Set goals for FB events
67.Implement Podcasts on FB
68. launching FB Events
69.Metrics for buyers and seller groups on FB
70.Design a product for gardening for Fb
71.define the goals and metrics for a live voice channel feature
72.FB Marketplace only for lending
73.set goals for bikers using Google Maps.
74.Design a product for health within FB blue app.
75.Build a product to find a doctor
76.What about FB Shops
77.PM for Instagram Stories. Goals and metrics?
78.video conferencing app
79.Build an app
80.Improve an established ride sharing product
81.How will you evaluate
82. Instagram Shopping
83.Product to enable people to offer/take help
84.how will you set the goals/metrics?
85.what will you build?
86.Design a Product for people to select cheese
87.Design a movie product for Facebook
88.PM for FB Search, define goals.
89.Design a product to develop and build hobby
90.Describe the metrics
91.find restaurants
92.a common goal
93.video streaming app
94.Build something for physical wellness
95.Measure success of FB Campus
96.SQL
97.Predict fraudulent
98.SQL
99.Array
100.LeetCode71
101.Video(watch)
102.Video(watch)
103.Feature
104.Fundrasier
105.LeetCode 1211
106.Composer
107.Search
108.Spam
109.Ads
110.Message
111.Friendship
112.Work Place
113. Facebook Shop
114.SMS Verification
115.Video(call/portal)
116.Posts
117. Dwell time/usage
118.SQL query
119.SQL case when
120.Ctr increase reasons
121.Hypothesis test
122.Improve product
123.Model basics
124.数组的运算
125.Coding test
126.SQL aggregation/ window function
127.SQL aggregation/ window function
128.ML model basic
129.贝叶斯/ stats
130.Product sense
131.SQL aggregation/ window function
132.SQL aggregation/ window function
133.Notification quality
134.Order, message and buyer
135.随机抽一个city nam
136.Restaurant you may like
137.Launch or not
138.Investigate quality of notification
139.how to improve Instagram Shopping
140.Avg waiting time for receiving new feature for each customer
141. Spam Friend Request
142.AB Test
143.Launch new functions
144.SQL aggregation/ filter
145.SQL functions
146.Product sense
147.Product sense
148.Bad actor
149.Dating
150.UI design metrics drop
151.Statistical Estimation without Assumptions
152.A/B Testing Case Study
153.SQL Query for Calculating Totals and Percentages
154.Medication Dispersion Variant
155.Sampling Cities Based on Population Proportions
156.Identify Bot Posts in a Multi-modal System
157.Explain your understanding of models and A/B testing in a product environment.
158.Data Analysis for Product Decisions
159.Percentage of Daily Active Users on Video Call
160.Identify Users Initiating Video Calls
161.Quantitative Analysis of Facebook Dating Metrics
162.Facebook Dating Product Advantages
163.Friend Request Sent and Acceptance Rate Calculation
164.Spam Friend Request Identification
165.Analysis of Changes in Likes and Matches on Facebook Dating
166.Facebook Dating Product Metrics
167.Friend Request Sent and Acceptance Rate Calculation
168.Spam Friend Request Identification
169.How do you approach problem-solving with data in a case where statistical content is minimal and case studies are more emphasized?
170.SQL Query for Friend Requests Over the Past Week
171.Recommendation System Design
172.Analytical Exercise on Network Effect
173.Product Evaluation for Facebook Dating
174.SQL Query for Hashtag Data
175.Product Case Analysis for Hashtag Recommendation
176.Nested Array Depth Multiplier
177.Optimal Solution for Finding Elements
178.Optimize Space Complexity in Letter Frequency Analysis
179.Find Most Frequent Letters in a String
180.Product Sense for Group Call Feature
181.SQL Query for Video Call Users
182.SQL Query for Group Calls
183.SQL TRUNCATE vs FLOOR
184.Metrics for Evaluating Recommendation Systems
185.Multi-task Classification for Ranking
186.Training Data Selection for Recall in Recommendation Systems
187.Design a Retrieval and Ranking Funnel
188.Data Requirements for Personalization in Recommendation Systems
189.Clarify User Interaction Types in a System
190.Design a Search System
191.Design an Ad Ranking System
192.Design a Recommendation System
193.Determine the number of active French users who made a call yesterday.
194.Calculate the number of people who called more than XX individuals in the past 7 days using SQL.
195.Coding Task: Implement KNN
196.Count the number of orders with messages from both buyer and seller
197.Count the number of orders with at least a message from the buyer by a specific date
198.Analyze the time spent distribution
199.Calculate the average number of sessions per user by day for the last 30 days
200.Reservoir Sampling Problem
201.Basic Calculator with Addition and Multiplication
202.Top K Frequent Elements in an Array
203.Global Ads Revenue SQL Problem
204.Circle Problem Prioritization
205.Advertising Impressions Distribution Problem
206.Product Case Analysis for Group Video Calls
207.SQL Query for User Engagement Analysis
208.SQL Query for User Call Analysis
209.Python Function to Find Most Frequent Theme in a Dictionary
210.Python Function to Find Smallest Odd Number
211.SQL Query for Author URL Percentage
212.SQL Query for Top 5 Customers Based on Invited Sales Value
213.SQL Query for Top 3 Payment Types by Total Sales
214.Analytical Execution
215.Comment Distribution Analysis
216.Random City Population Generator
217.Moving Average from Data Stream
218.Interpreting A/B Test Results
219.Investigating a Drop in Click-Through Rate
220.Analyzing Survey Response Rate and User Opinion on Notifications
221.Evaluating a New Notification Feature
222.Determining the Quality of Notifications
223.Statistical Distribution Analysis
224.SQL Reporting Query
225.Measuring Feature Performance
226.Metrics to Measure Feature Performance
227.User Interest for Group Call Feature
228.Analysis of Active Users of Call Function in France
229.Approach to a metrics drop in a Facebook product
230.How to evaluate a recommendation system?
231.How to calculate the average number of conversations from given message-related tables?
232.Defining New and Tenure Users Without CTE
233.Experiment Design with ML Classification
234.Group Comment SQL Problem
235.Calculator Problem
236.Find Numbers Lower Than Neighbors
237.Sum of Numbers in a Sliding Window
238.SQL Queries for Non-Compliant Content Analysis
239.Identifying Non-Compliant Content on Meta Platforms
240.Distribution of Shop Categories on Instagram
241.Classifier Model Launch Decision
242.Probability of Fake Friends Requests
243.Bad Account Friend Request Analysis
244.Restaurant Recommendation Algorithm
245.Calculate the Percentage of Users with a High Probability of Recidivism
246.Calculate the Number of Users for Each Banned Reason from Last 7 Days
247.Daily Active Users (DAU) Calculation
248.Flight Itinerary Reconstruction
249.Impact of Launching Video Call on Metrics
250.Measuring Control Group Without Video Call Feature
251.Machine Learning Design Interview Question
252.Product Case Interview Question
253.Python Coding Interview Question
254.SQL Coding Interview Question
255.Detecting and Evaluating Harmful Content
256.Count of Posts with Views Exceeding a Threshold
257.Find the minimum sum of two arrays representing departure and return ticket prices
258.Simple Arithmetic Coding Problem
259.Calculate the Percentage of Daily Active Users on a Video Call
260.Cheapest Round-Trip Flight Price
261.Product Case Deep Dive
262.SQL Query for Visualization Plot
263.SQL Filtering Condition
264.Kth Largest Number in Array Using QuickSelect
265.Deciding to Launch a New Notification Feature
266.Evaluating the Effectiveness of Notifications
267.Largest Audience in Simultaneous Meetings
268.Most Common Theme in Book Titles
269.Authors with 'http://' Prefix and No Sales
270.Top Customers by Sales Value of Invited People
271.Total Number of Sold Books by Payment Type
272.Nested List Weight Sum
273.Moving Average from Data Stream
274.SQL Query for Reporting Percentage of College Students
275.SQL Query for Ranking Countries by College Users
276.Detecting College Students Among IG Users
277.Pathfinding in a 2D Matrix with Obstacles
278.Optimal Round-Trip Flight Date Selection
279.Antonym Extraction with Single Deletion
280.SQL Survey Query
281.Sampling Problem with Reservoir Sampling Follow-up
282.All Subarrays with Sum Equals Target
283.Matrix Row or Column Sum Equals Target
284.Subarray Sum Equals Target
285.Calculate CTR using SQL
286.Merge 3 Sorted Lists Using Pointers
