分享下亚马逊Advertisting 部门的Tech Bar

上周和亚马逊Advertisting 的同事聊了一下，她很热心的分享了他们招人的tech bar， 包括Marketing Science 和 Data Science 两部分。这个list 很全面，但面试的时候只是选几个自己的强项考核。希望对大家有帮助，求大米:)


1. Marketing Science Methodologies
a) Basics of Descriptive Analytics:
i. Measures of central tendency (mean, median, mode)
ii. Measures of spread (range, standard deviation)
iii. Quantiles and inter-quantile distance
b) Basics of Probability:
i. Calculate probability of union and intersection of multiple of events
. 1point3acres.com ii. Ability to use Bayes Theorem
iii. Know the difference between independent and un-correlated random variables
iv. Simple combinatorics, e.g., probability of 4 aces in deck of cards
c) Basic Probability Distributions:
i. What is a probability distribution function? (Univariate)
ii. Understanding differences between basic continuous distributions (e.g. uniform, normal, exponential: memoryless property).
iii. Understanding basic discrete distributions (e.g. Bernoulli or coin toss)
iv. What is mean/variance?
d) Basics of Estimation and Hypothesis Testing:
i. Recognize difference between population parameters versus sample statistic
ii. Ideas behind simple Hypothesis Testing and its relation to Confidence Intervals
iii. Type 1 error, Type II error
iv. P-values, statistical significance
v. Basics of A/B testing.
e) Basics of Regression:
i. Concepts, and terminology
ii. Simple linear regression model, assumptions, Ordinary Least Squares (OLS)
f) Basics of Forecasting:
iii. Moving Averages
iv. Serial correlation and seasonality

2. Data Science Disciplines

a) Data Analysis:
i. Best practices for displaying data
ii. Boxplots
iii. Scatterplots
iv. Contingency tables (2x2 tables)
v. Simpson’s paradox
vi. Regression to the mean
vii. Data manipulation questions (e.g., wide to long format conversions, creation of graphs that require non-trivial data manipulation)
viii. QQ-plots
ix. Histograms
x. Dimension reduction techniques (e.g., PCA)
b) Estimation and Hypothesis Testing:
i. Frequentist sampling concepts
ii. Simple random sample (SRS) definition
iii. Properties of estimators, bias and variance
iv. Power
v. Confidence interval interpretation
vi. Multiple testing issues (familywise error, Bonferroni, FDR)
vii. One-sample versus two-sample hypothesis testing, paired versus unpaired data tests
viii. Test for proporti

您好！
本帖隐藏的内容需要积分高于 188 才可浏览
您当前积分为 0。
使用VIP即刻解锁阅读权限或查看其他获取积分的方式

游客，您好！
本帖隐藏的内容需要积分高于 188 才可浏览
您当前积分为 0。
VIP即刻解锁阅读权限 或 查看其他获取积分的方式
Unlock interview details and practice with AI
Curated Interview Questions from Top Companies

ching
ii. Look-alike modelling
iii. Programmatic advertising
iv. Search engine optimization methods
h) Market Structure:
i. Types of Market Structure (e.g. Perfect competition, Monopoly, Oligopoly, Monopolistic competition, Contestable markets)
ii. Market Concentration Measures (e.g. N-firm concentration ratio, Herfindahl-Hirschman Index)
iii. Market Analysis Dimensions (e.g. Market size, Market trends, Market growth rate, Market profitability, Industry cost structure, Distribution channels)
iv. Market Research Techniques (e.g. Secondary Data Sources, Unstructured Research, Surveys)
i) Online Content:
i. User-generated or professional content: natural language processing (volume, sentiment and topic analysis)
ii. Representativeness of online content (e.g. customer reviews): self-selection, extremes bias, J-shaped star ratings
iii. Influence on brand reputation plus as input to media planning
j) Product launch:
i. Product innovation, quality improvements and differences in customer vs manufacturer perception of these terms
ii. New product diffusion at aggregate (diffusion model) and audience segmentation level (innovators, early adopters…)
iii. Drivers of successful new product launch: roles of customer information, perceived risk, product price and advertising

请问楼主这个适用于ads下面的BIE吗？

谢谢分享， 真棒！

zan!

leeshuang0821 发表于 2021-03-18 21:21:30
请问楼主这个适用于ads下面的BIE吗？

BIE 应该不是这个要求，我对热带雨林BIE的理解是更多datamart tables, Tableau dashboard，或各种reports 搭建，建模或分析会比较少。

艹这个真的是统计phd level了，很多都是比较热门的研究方向

看到这个list我只想说，data方面的面试范围是真的广！

请问是否适用于Data engineer的岗位呢？谢谢～

赞楼主！！ 很有用的信息！

面的l5，面完反馈可能会被降级，还有l4的hc吗