1.Dense Rank vs Rank
2.SQL join中的where和on的区别
3.抛硬币的概率计算
4.ios12和ios13开机时间测试
5.Center计算
6.How to define KPIs for an App
7.How to define the relevane of search results
8.Project experience
9.Text Classification模型
10.DAU计算
11.Launch or not
12.AB Test如何检测robustness和sensitivity
13.LTV计算
14.计算字母数
15.full join考察
16.Merge Two Sorted Lists
17.Wildcard Matching
18.SQL基础
19.SQL基础
20.Candy Crush
21.中位数
22.Word Ladder
23.日期间隔计算
24.Count of Smaller Numbers After Self
25.leetcode694
26.Number of Islands
27.Split Linked List in Parts
28.Spiral Matrix
29.Merge k Sorted Lists
30.Max Version
31.Subarray Sum Equals K
32.Integer to English Words
33.Measure steps with Apple watch
34.List operation
35.Commit fraud
36.apple wallet vulnerability
37.payment fraud mitigation solution
38.Basic SQL questions
39.Why power increases when amount of data decreases
40.Caan we launch feature in those countries which are statistically significant
41.Can we stop the experiment when p-value becomes statistical significant before the experiment ends
42.Factors of experiment running time
43.What will p-value change when samples changed
44.Compare proportion of two population
45.Output results based on some requirements
46.How to evaluate new features
47.Evaluate the change of students' scores after a program
48.How to shorten confidence interval
49.Best Time to Buy and Sell Stock
50.Coding Challenge
51.Identifying Anomalous Account Login Behavior
52.Case Study: Impact of Financial Aid on Education Investment
53.Identifying Overfitting in a Model
54.Explaining Overfitting to a Business Partner
55.Reporting Metrics for Fraud Detection
56.Designing a Spam Detector
57.Hypothetical Work Scenarios
58.SQL Window Function Usage
59.Dealing with App Store Malicious Positive Reviews
60.Handling False Positives in Fraud Prevention
61.Retention Analysis Case Study
62.Advanced SQL Coding Challenge
63.Knowledge of Computer Vision and Machine Learning courses
64.Explain a project from your resume and its difficulties
65.Discuss your internship project related to Machine Learning
66.Committing Fraud Hypothetical Case
67.Dashboard Design
68.Python Coding for Palindrome
69.SQL Query Writing
70.Fraud Case Analysis
71.Discuss the tools you use for production quality analysis.
72.Explain how you deal with vendors providing non-qualified parts.
73.Discuss your approach to improving quality.
74.Describe your experience with final assembly and managing multiple assembly lines.
75.Explain CPK and CP in the context of quality control.
76.Describe a situation where you had to handle a late critical part.
77.Discuss your method for improving product yield.
78.Describe your approach to managing a manufacturing line.
79.Explain the concepts of strength and stiffness in materials.
80.ML Design for Evaluating NLP Tasks
81.Statistical Foundations and A/B Testing
82.AB Testing
83.Data Pipeline Experience
84.KPI Analysis
85.SQL Query Formulation
86.Interpreting A/B Test Results
87.Designing an A/B Testing Framework
88.Difference between boosting and bagging
89.Implement Precision Recall Curve
90.Query Disambiguation and Segmentation
91.Improve Diversity in Recommendations
92.Bayesian Probability Calculation
93.SQL Query for Average Time Spent Per User
94.Calculating Power in A/B Testing
95.Understanding Type I and Type II Errors
96.Identifying Outliers in Daily Metrics
97.Metric Design for Search Product
98.Basic SQL Join and Where
99.Normal Distribution of 2X+Y
100.Modeling for Siri User Satisfaction
101.Siri Customer Satisfaction Analysis
102.Optimizing Large Data Processing
103.Machine Learning System Design
104.Machine Learning Workflow Knowledge
105.Advanced Python Programming for Data Science
106.Strategies for achieving high CPK levels in your company.
107.Discuss cases of variable and attribute in GR&R.
108.Approach to determining and solving tolerance issues in design.
109.Differentiate between CP and CPK and the advantages of using CPK.
110.Describe the basic process of GR&R and how to handle failures.
111.Explain the concept of GD&T and its importance in quality engineering.
112.Describe a project you have worked on and the difficulties faced
113.Discuss an internship project, the models used, and the difficulties encountered
114.Machine Learning Application Coding
115.Multimodal Prediction Problem
116.Machine Learning Project Discussion
117.Tag Recommendation System
118.Top 5 Contents by Months by Country by Paid Plans
119.2019 Monthly Trend of Active Paid Subscriptions
120.Segmenting Users
121.Bias-Variance Tradeoff and Overfitting
122.Time Series Model and ACF/PACF
123.Propensity Model and Beta Estimates Calculation
124.Difference Between Random Forest and XGBoost
125.Count Daily Active Users on Each Platform
126.Implement and Optimize K-means Algorithm
127.Number of Users Whose First Play is in April 2021
128.Number of Users Visited Pages but Didn’t Play
129.Number of Cross-Platform Viewers
130.Difference Between RANK and DENSE_RANK in SQL
131.SQL Join and Basic Filtering
132.AB Testing Group Sample Size Sanity Check
133.TextProcessor Class with Cosine Similarity Method
134.Python Class for Text Document Analysis
135.Python Function for Mean, Median, and Mode
136.SQL Query for Top 2 Amounts Spent by Each User
137.SQL Query for Total Amount Spent by Apple Pay Users vs Non-Apple Pay Users
138.Increased Power with Reduced Data Exposure
139.Launching Features Based on Country-Specific Results
140.Early Termination of an Experiment with Significant Results
141.Factors Affecting the Duration of an Experiment
142.Effect of Sample Proportion Changes on P-Value
143.Comparing Two Population Proportions
144.Bi-gram Count in Page Titles
145.Identifying the Most Visited Domain
146.Unique Domain Extraction from URLs
147.Evaluating New Search Features
148.Evaluating Student Performance Changes
149.Reducing the Confidence Interval to a Tenth of Its Original Size
150.Choosing Between Device Level CTR and Impression CTR
151.Handling Positively Skewed Distributions
152.Statistical Concepts
153.SQL Query for Highest Click-Through Rate
154.Random Permutation Using Numpy
155.Machine Learning Algorithms and Data Experience
156.Understanding ACID Properties
157.Visualization Design
158.SQL Join Types
159.SQL Window Function and Group By
160.Recommendation System Case Study
161.Data Challenge and Presentation
162.SQL Coding Round
163.Create a Generator for Random Email Addresses and Phone Numbers
164.Case Study: Unbiased Testing of AirPods Design Satisfaction
165.Python Coding Exercise
