SlideShare a Scribd company logo
Jianqiang (Jay) Wang
Feb 21, 2015
Preparing for Technical
Interview
About me
B.S. degree in Management Science and Ph.D. in
Statistics
Data scientist in twitter ads-ranking
HP Labs : pricing & portfolio management, marketing,
USDA : yield forecasting with satellite & survey data
Instructor at Colorado State University
Innovations in the intersection of statistics, computer
science and business
Applications in online advertising and e-commerce.
Interview experiences:
Google, LinkedIn, Apple, FB, twitter;
startup positions;
Phone screening (whiteboard coding, experiences,
technical problems at high level)
Business insights
Algorithm design
Analytics questions
Statistics : concepts and methods
Technical skills : SQL/R/Hadoop
Interview experiences
Business insight questions
Think of ways of monetizing on WhatsApp?
Propose a new Yelp feature?
How to grow twitter monthly active users (MAU)?
Recent news about the company & competitors
Sign up and use their core products
Keep informed of news in your interested industry
Analytical questions
Hypothetical problem to analyze & reason
Define metrics
Hypothesize possible reasons
Estimate effects of various factors
Suppose pinterest wants to associate a price tag with
each pin, how to evaluate whether this works?
Analytical : think like a data scientist
What are possible causes that average time spent per
user drops after this launch?
How do you find out the root cause(s)?
Finding pattern in data
Tease out signals from noise
Hypothesis testing
Time series analysis
Estimate the effects of various factors
Regression
A/B testing
Computer simulation
Statistics : concepts
Mean, median, mode, quantile.
Variance, range, IQR, covariance, correlation.
p-value, likelihood function.
How do you explain confidence interval to an engineer?
What’s Bayes theorem? Examples?
Gender-disease example.
Microsoft bing example: better new algorithm .1%, test significant
5% of time under H0, and 20% of time under alternative.
Statistics : methods
Show the same twitter ads to 2,000 users, and 15 users
clicked, CTR?
What is multi-colinearity?
What’s the difference between stratified & cluster
sampling?
Completely randomized block design? Give an example?
Signup completion on FB.
Book : statistical sleuth.
Coursera statistics classes.
Brain teaser
Suppose you are given an unfair coin, how can you get
probability of ½?
Put 50 black balls and 50 white balls into 2 buckets.
Randomly select a bucket and then a ball in the
bucket. How to maximize the prob of choosing black?
Given a fair die with 6 faces, how do you randomly
generate numbers between 1 and 12?
Programming: Rand6() -> Rand12().
Whiteboard coding (DS)
Suppose the amount we charge on ad clicks comes in a
stream. Write a program to calculate cumulative cost.
Correlation : (per ad cost, size of display)?
Write a program to simulate M:F ratio assuming each
family stops giving birth after the first boy (no twins).
CS coding & algorithm complexity: given an array of
numbers, find two that the sum is closest to 0?
Leetcode & cracking the coding interview
Practice with paper & pencil!
Data manipulations
Excel
SQL
Scripting language like R or python.
Dataset with (gender, age, time spent on FB per day)
Create age buckets: (0, 10], (10, 20], ...
Average time spent for each (gender, age bucket).
Table joins: inner join, left/right join, outer join (SQL & R)
Resources
Books
Statistical sleuth
Big data governance (quality, privacy, application in various verticals)
Data just right (DS)
the Startup of you
7 habits of highly effective people
Quora post : how to become a data scientist
Coursera classes
Intro to statistics
R programming
Machine learning
Intro to data science
Web intelligence and big data (DS)
glassdoor, careercup,...
Crawl twitter data in R (or python)
user info
user tweets
user network
Search results;
Text analytics (+ optional : predictive task)
Frequency of n-grams
Remove trivial words
Find associated entities
Visualization
Associative words
Sentiment
Volume
Interactive app : specify time window or specify entity, display raw
tweets, show volume by time
Twitter data analytics
Projects
Linkedin data;
Twitter data: targeting people who wants to
buy air tickets;

More Related Content

What's hot

Predictive Analytics: An Executive Primer
Predictive Analytics: An Executive PrimerPredictive Analytics: An Executive Primer
Predictive Analytics: An Executive Primer
Ryan Withop
 
1305 track 3 siegel
1305 track 3 siegel1305 track 3 siegel
1305 track 3 siegel
Rising Media, Inc.
 
“Improving” prediction of human behavior using behavior modification
“Improving” prediction of human behavior using behavior modification“Improving” prediction of human behavior using behavior modification
“Improving” prediction of human behavior using behavior modification
Galit Shmueli
 
Data Science for Business Managers - The bare minimum a manager should know
Data Science for Business Managers - The bare minimum a manager should knowData Science for Business Managers - The bare minimum a manager should know
Data Science for Business Managers - The bare minimum a manager should know
Akin Osman Kazakci
 
Digital analytics lecture4
Digital analytics lecture4Digital analytics lecture4
Digital analytics lecture4
Joni Salminen
 
Business Intelligence & Predictive Analytic by Prof. Lili Saghafi
Business Intelligence & Predictive Analytic by Prof. Lili SaghafiBusiness Intelligence & Predictive Analytic by Prof. Lili Saghafi
Business Intelligence & Predictive Analytic by Prof. Lili Saghafi
Professor Lili Saghafi
 
Predictive Marketing Analytics
Predictive Marketing AnalyticsPredictive Marketing Analytics
Predictive Marketing Analytics
Lori Fisher
 
Data Analytics in Azure Cloud
Data Analytics in Azure CloudData Analytics in Azure Cloud
Data Analytics in Azure Cloud
Microsoft Canada
 
predictive analytics
predictive analyticspredictive analytics
predictive analytics
Astha Jagetiya
 
¿Como los modelos predictivos cambian los negocios?
¿Como los modelos predictivos cambian los negocios?¿Como los modelos predictivos cambian los negocios?
¿Como los modelos predictivos cambian los negocios?
Fabricio Quintanilla
 
Machine Learning for Sales & Marketing
Machine Learning for Sales & MarketingMachine Learning for Sales & Marketing
Machine Learning for Sales & Marketing
Piyush Saggi
 
Machine Learning in Retail: Know Your Customers' Customer. See Your Future
Machine Learning in Retail: Know Your Customers' Customer. See Your FutureMachine Learning in Retail: Know Your Customers' Customer. See Your Future
Machine Learning in Retail: Know Your Customers' Customer. See Your Future
BigML, Inc
 
PREDICTION OF CRUDE OIL PRICES USING SVR WITH GRID SEARCH CROSS VALIDATION AL...
PREDICTION OF CRUDE OIL PRICES USING SVR WITH GRID SEARCH CROSS VALIDATION AL...PREDICTION OF CRUDE OIL PRICES USING SVR WITH GRID SEARCH CROSS VALIDATION AL...
PREDICTION OF CRUDE OIL PRICES USING SVR WITH GRID SEARCH CROSS VALIDATION AL...
Venkat Projects
 
achine Learning and Model Risk
achine Learning and Model Riskachine Learning and Model Risk
achine Learning and Model Risk
QuantUniversity
 
Behavioral Big Data & Healthcare Research
Behavioral Big Data & Healthcare ResearchBehavioral Big Data & Healthcare Research
Behavioral Big Data & Healthcare Research
Galit Shmueli
 
Prognosis - An Approach to Predictive Analytics- Impetus White Paper
Prognosis - An Approach to Predictive Analytics- Impetus White PaperPrognosis - An Approach to Predictive Analytics- Impetus White Paper
Prognosis - An Approach to Predictive Analytics- Impetus White Paper
Impetus Technologies
 
ForresterPredictiveWave
ForresterPredictiveWaveForresterPredictiveWave
ForresterPredictiveWave
Timothy M. Caffrey, MBA
 
Decision Intelligence: a new discipline emerges
Decision Intelligence: a new discipline emergesDecision Intelligence: a new discipline emerges
Decision Intelligence: a new discipline emerges
Lorien Pratt
 
Future of marketing research
Future of marketing researchFuture of marketing research
Future of marketing research
Ayesha Saeed Haq
 
Perspectives on Machine Learning
Perspectives on Machine LearningPerspectives on Machine Learning
Perspectives on Machine Learning
Dr. Niren Sirohi
 

What's hot (20)

Predictive Analytics: An Executive Primer
Predictive Analytics: An Executive PrimerPredictive Analytics: An Executive Primer
Predictive Analytics: An Executive Primer
 
1305 track 3 siegel
1305 track 3 siegel1305 track 3 siegel
1305 track 3 siegel
 
“Improving” prediction of human behavior using behavior modification
“Improving” prediction of human behavior using behavior modification“Improving” prediction of human behavior using behavior modification
“Improving” prediction of human behavior using behavior modification
 
Data Science for Business Managers - The bare minimum a manager should know
Data Science for Business Managers - The bare minimum a manager should knowData Science for Business Managers - The bare minimum a manager should know
Data Science for Business Managers - The bare minimum a manager should know
 
Digital analytics lecture4
Digital analytics lecture4Digital analytics lecture4
Digital analytics lecture4
 
Business Intelligence & Predictive Analytic by Prof. Lili Saghafi
Business Intelligence & Predictive Analytic by Prof. Lili SaghafiBusiness Intelligence & Predictive Analytic by Prof. Lili Saghafi
Business Intelligence & Predictive Analytic by Prof. Lili Saghafi
 
Predictive Marketing Analytics
Predictive Marketing AnalyticsPredictive Marketing Analytics
Predictive Marketing Analytics
 
Data Analytics in Azure Cloud
Data Analytics in Azure CloudData Analytics in Azure Cloud
Data Analytics in Azure Cloud
 
predictive analytics
predictive analyticspredictive analytics
predictive analytics
 
¿Como los modelos predictivos cambian los negocios?
¿Como los modelos predictivos cambian los negocios?¿Como los modelos predictivos cambian los negocios?
¿Como los modelos predictivos cambian los negocios?
 
Machine Learning for Sales & Marketing
Machine Learning for Sales & MarketingMachine Learning for Sales & Marketing
Machine Learning for Sales & Marketing
 
Machine Learning in Retail: Know Your Customers' Customer. See Your Future
Machine Learning in Retail: Know Your Customers' Customer. See Your FutureMachine Learning in Retail: Know Your Customers' Customer. See Your Future
Machine Learning in Retail: Know Your Customers' Customer. See Your Future
 
PREDICTION OF CRUDE OIL PRICES USING SVR WITH GRID SEARCH CROSS VALIDATION AL...
PREDICTION OF CRUDE OIL PRICES USING SVR WITH GRID SEARCH CROSS VALIDATION AL...PREDICTION OF CRUDE OIL PRICES USING SVR WITH GRID SEARCH CROSS VALIDATION AL...
PREDICTION OF CRUDE OIL PRICES USING SVR WITH GRID SEARCH CROSS VALIDATION AL...
 
achine Learning and Model Risk
achine Learning and Model Riskachine Learning and Model Risk
achine Learning and Model Risk
 
Behavioral Big Data & Healthcare Research
Behavioral Big Data & Healthcare ResearchBehavioral Big Data & Healthcare Research
Behavioral Big Data & Healthcare Research
 
Prognosis - An Approach to Predictive Analytics- Impetus White Paper
Prognosis - An Approach to Predictive Analytics- Impetus White PaperPrognosis - An Approach to Predictive Analytics- Impetus White Paper
Prognosis - An Approach to Predictive Analytics- Impetus White Paper
 
ForresterPredictiveWave
ForresterPredictiveWaveForresterPredictiveWave
ForresterPredictiveWave
 
Decision Intelligence: a new discipline emerges
Decision Intelligence: a new discipline emergesDecision Intelligence: a new discipline emerges
Decision Intelligence: a new discipline emerges
 
Future of marketing research
Future of marketing researchFuture of marketing research
Future of marketing research
 
Perspectives on Machine Learning
Perspectives on Machine LearningPerspectives on Machine Learning
Perspectives on Machine Learning
 

Similar to How to prepare for data science interviews

From Rocket Science to Data Science
From Rocket Science to Data ScienceFrom Rocket Science to Data Science
From Rocket Science to Data Science
Sanghamitra Deb
 
Science to Data Science: PhDs and postdocs moving to startups and industry (2...
Science to Data Science: PhDs and postdocs moving to startups and industry (2...Science to Data Science: PhDs and postdocs moving to startups and industry (2...
Science to Data Science: PhDs and postdocs moving to startups and industry (2...
AI Guild
 
Career_Jobs_in_Data_Science.pptx
Career_Jobs_in_Data_Science.pptxCareer_Jobs_in_Data_Science.pptx
Career_Jobs_in_Data_Science.pptx
HarpreetSharma14
 
Bayesian reasoning
Bayesian reasoningBayesian reasoning
Bayesian reasoning
Marta Fajlhauer
 
How to Start Doing Data Science
How to Start Doing Data ScienceHow to Start Doing Data Science
How to Start Doing Data Science
Ayodele Odubela
 
UXPA 2016: Mixed Methods Research in the Age of Big Data
UXPA 2016: Mixed Methods Research in the Age of Big DataUXPA 2016: Mixed Methods Research in the Age of Big Data
UXPA 2016: Mixed Methods Research in the Age of Big Data
Zachary Sam Zaiss
 
Data Analysis - Making Big Data Work
Data Analysis - Making Big Data WorkData Analysis - Making Big Data Work
Data Analysis - Making Big Data Work
David Chiu
 
Brochure data science learning path board-infinity (1)
Brochure   data science learning path board-infinity (1)Brochure   data science learning path board-infinity (1)
Brochure data science learning path board-infinity (1)
NirupamNishant2
 
Machine Learning - Challenges, Learnings & Opportunities
Machine Learning - Challenges, Learnings & OpportunitiesMachine Learning - Challenges, Learnings & Opportunities
Machine Learning - Challenges, Learnings & Opportunities
CodePolitan
 
Data Con LA 2022 - Demystifying the Art of Business Intelligence and Data Ana...
Data Con LA 2022 - Demystifying the Art of Business Intelligence and Data Ana...Data Con LA 2022 - Demystifying the Art of Business Intelligence and Data Ana...
Data Con LA 2022 - Demystifying the Art of Business Intelligence and Data Ana...
Data Con LA
 
Accelerate: AI Trends in 2018
Accelerate: AI Trends in 2018Accelerate: AI Trends in 2018
Accelerate: AI Trends in 2018
Aarthi Srinivasan
 
Data science presentation
Data science presentationData science presentation
Data science presentation
MSDEVMTL
 
Guide for a Data Scientist
Guide for a Data ScientistGuide for a Data Scientist
Guide for a Data Scientist
Rohit Dubey
 
Data science and Machine learning Booklet
Data science and Machine learning BookletData science and Machine learning Booklet
Data science and Machine learning Booklet
Vellore Institute of Technology
 
Assignment of data science ds4 mubeen
Assignment of data science ds4 mubeenAssignment of data science ds4 mubeen
Assignment of data science ds4 mubeen
mubeenasghar3
 
Data Science Crash course
Data Science Crash courseData Science Crash course
Data Science Crash course
Mohamed Essam
 
Startds9.19.17sd
Startds9.19.17sdStartds9.19.17sd
Startds9.19.17sd
Thinkful
 
Eric Smidth
Eric SmidthEric Smidth
Formulating career path in data science (1)
Formulating career path in data science (1)Formulating career path in data science (1)
Formulating career path in data science (1)
Kennedy Kamande Wangari
 
How to build a career in data science / AI / ML
How to build a career in data science / AI / ML How to build a career in data science / AI / ML
How to build a career in data science / AI / ML
Swathi Young
 

Similar to How to prepare for data science interviews (20)

From Rocket Science to Data Science
From Rocket Science to Data ScienceFrom Rocket Science to Data Science
From Rocket Science to Data Science
 
Science to Data Science: PhDs and postdocs moving to startups and industry (2...
Science to Data Science: PhDs and postdocs moving to startups and industry (2...Science to Data Science: PhDs and postdocs moving to startups and industry (2...
Science to Data Science: PhDs and postdocs moving to startups and industry (2...
 
Career_Jobs_in_Data_Science.pptx
Career_Jobs_in_Data_Science.pptxCareer_Jobs_in_Data_Science.pptx
Career_Jobs_in_Data_Science.pptx
 
Bayesian reasoning
Bayesian reasoningBayesian reasoning
Bayesian reasoning
 
How to Start Doing Data Science
How to Start Doing Data ScienceHow to Start Doing Data Science
How to Start Doing Data Science
 
UXPA 2016: Mixed Methods Research in the Age of Big Data
UXPA 2016: Mixed Methods Research in the Age of Big DataUXPA 2016: Mixed Methods Research in the Age of Big Data
UXPA 2016: Mixed Methods Research in the Age of Big Data
 
Data Analysis - Making Big Data Work
Data Analysis - Making Big Data WorkData Analysis - Making Big Data Work
Data Analysis - Making Big Data Work
 
Brochure data science learning path board-infinity (1)
Brochure   data science learning path board-infinity (1)Brochure   data science learning path board-infinity (1)
Brochure data science learning path board-infinity (1)
 
Machine Learning - Challenges, Learnings & Opportunities
Machine Learning - Challenges, Learnings & OpportunitiesMachine Learning - Challenges, Learnings & Opportunities
Machine Learning - Challenges, Learnings & Opportunities
 
Data Con LA 2022 - Demystifying the Art of Business Intelligence and Data Ana...
Data Con LA 2022 - Demystifying the Art of Business Intelligence and Data Ana...Data Con LA 2022 - Demystifying the Art of Business Intelligence and Data Ana...
Data Con LA 2022 - Demystifying the Art of Business Intelligence and Data Ana...
 
Accelerate: AI Trends in 2018
Accelerate: AI Trends in 2018Accelerate: AI Trends in 2018
Accelerate: AI Trends in 2018
 
Data science presentation
Data science presentationData science presentation
Data science presentation
 
Guide for a Data Scientist
Guide for a Data ScientistGuide for a Data Scientist
Guide for a Data Scientist
 
Data science and Machine learning Booklet
Data science and Machine learning BookletData science and Machine learning Booklet
Data science and Machine learning Booklet
 
Assignment of data science ds4 mubeen
Assignment of data science ds4 mubeenAssignment of data science ds4 mubeen
Assignment of data science ds4 mubeen
 
Data Science Crash course
Data Science Crash courseData Science Crash course
Data Science Crash course
 
Startds9.19.17sd
Startds9.19.17sdStartds9.19.17sd
Startds9.19.17sd
 
Eric Smidth
Eric SmidthEric Smidth
Eric Smidth
 
Formulating career path in data science (1)
Formulating career path in data science (1)Formulating career path in data science (1)
Formulating career path in data science (1)
 
How to build a career in data science / AI / ML
How to build a career in data science / AI / ML How to build a career in data science / AI / ML
How to build a career in data science / AI / ML
 

More from Jay (Jianqiang) Wang

Artificial Intelligence in fashion -- Combining Statistics and Expert Human J...
Artificial Intelligence in fashion -- Combining Statistics and Expert Human J...Artificial Intelligence in fashion -- Combining Statistics and Expert Human J...
Artificial Intelligence in fashion -- Combining Statistics and Expert Human J...
Jay (Jianqiang) Wang
 
Making data-informed decisions and building intelligent products (Chinese)
Making data-informed decisions and building intelligent products (Chinese)Making data-informed decisions and building intelligent products (Chinese)
Making data-informed decisions and building intelligent products (Chinese)
Jay (Jianqiang) Wang
 
Notes on Machine Learning and Data-centric Startups
Notes on Machine Learning and Data-centric StartupsNotes on Machine Learning and Data-centric Startups
Notes on Machine Learning and Data-centric Startups
Jay (Jianqiang) Wang
 
Boosted multinomial logit model (working manuscript)
Boosted multinomial logit model (working manuscript)Boosted multinomial logit model (working manuscript)
Boosted multinomial logit model (working manuscript)
Jay (Jianqiang) Wang
 
Boosted Tree-based Multinomial Logit Model for Aggregated Market Data
Boosted Tree-based Multinomial Logit Model for Aggregated Market DataBoosted Tree-based Multinomial Logit Model for Aggregated Market Data
Boosted Tree-based Multinomial Logit Model for Aggregated Market Data
Jay (Jianqiang) Wang
 
Multivariate outlier detection
Multivariate outlier detectionMultivariate outlier detection
Multivariate outlier detection
Jay (Jianqiang) Wang
 
Multivariate outlier detection
Multivariate outlier detectionMultivariate outlier detection
Multivariate outlier detection
Jay (Jianqiang) Wang
 
A Bayesian Approach to Estimating Agricultual Yield Based on Multiple Repeat...
A Bayesian Approach to Estimating Agricultual Yield Based on Multiple Repeat...A Bayesian Approach to Estimating Agricultual Yield Based on Multiple Repeat...
A Bayesian Approach to Estimating Agricultual Yield Based on Multiple Repeat...
Jay (Jianqiang) Wang
 

More from Jay (Jianqiang) Wang (8)

Artificial Intelligence in fashion -- Combining Statistics and Expert Human J...
Artificial Intelligence in fashion -- Combining Statistics and Expert Human J...Artificial Intelligence in fashion -- Combining Statistics and Expert Human J...
Artificial Intelligence in fashion -- Combining Statistics and Expert Human J...
 
Making data-informed decisions and building intelligent products (Chinese)
Making data-informed decisions and building intelligent products (Chinese)Making data-informed decisions and building intelligent products (Chinese)
Making data-informed decisions and building intelligent products (Chinese)
 
Notes on Machine Learning and Data-centric Startups
Notes on Machine Learning and Data-centric StartupsNotes on Machine Learning and Data-centric Startups
Notes on Machine Learning and Data-centric Startups
 
Boosted multinomial logit model (working manuscript)
Boosted multinomial logit model (working manuscript)Boosted multinomial logit model (working manuscript)
Boosted multinomial logit model (working manuscript)
 
Boosted Tree-based Multinomial Logit Model for Aggregated Market Data
Boosted Tree-based Multinomial Logit Model for Aggregated Market DataBoosted Tree-based Multinomial Logit Model for Aggregated Market Data
Boosted Tree-based Multinomial Logit Model for Aggregated Market Data
 
Multivariate outlier detection
Multivariate outlier detectionMultivariate outlier detection
Multivariate outlier detection
 
Multivariate outlier detection
Multivariate outlier detectionMultivariate outlier detection
Multivariate outlier detection
 
A Bayesian Approach to Estimating Agricultual Yield Based on Multiple Repeat...
A Bayesian Approach to Estimating Agricultual Yield Based on Multiple Repeat...A Bayesian Approach to Estimating Agricultual Yield Based on Multiple Repeat...
A Bayesian Approach to Estimating Agricultual Yield Based on Multiple Repeat...
 

Recently uploaded

Malana- Gimlet Market Analysis (Portfolio 2)
Malana- Gimlet Market Analysis (Portfolio 2)Malana- Gimlet Market Analysis (Portfolio 2)
Malana- Gimlet Market Analysis (Portfolio 2)
TravisMalana
 
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
nuttdpt
 
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
一比一原版(UofS毕业证书)萨省大学毕业证如何办理一比一原版(UofS毕业证书)萨省大学毕业证如何办理
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
v3tuleee
 
My burning issue is homelessness K.C.M.O.
My burning issue is homelessness K.C.M.O.My burning issue is homelessness K.C.M.O.
My burning issue is homelessness K.C.M.O.
rwarrenll
 
一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理
一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理
一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理
dwreak4tg
 
The affect of service quality and online reviews on customer loyalty in the E...
The affect of service quality and online reviews on customer loyalty in the E...The affect of service quality and online reviews on customer loyalty in the E...
The affect of service quality and online reviews on customer loyalty in the E...
jerlynmaetalle
 
一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理
一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理
一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理
g4dpvqap0
 
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
nuttdpt
 
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
bopyb
 
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
Timothy Spann
 
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
slg6lamcq
 
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
sameer shah
 
Learn SQL from basic queries to Advance queries
Learn SQL from basic queries to Advance queriesLearn SQL from basic queries to Advance queries
Learn SQL from basic queries to Advance queries
manishkhaire30
 
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
slg6lamcq
 
Intelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicineIntelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicine
AndrzejJarynowski
 
The Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series DatabaseThe Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series Database
javier ramirez
 
Influence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business PlanInfluence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business Plan
jerlynmaetalle
 
一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理
一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理
一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理
mbawufebxi
 
Nanandann Nilekani's ppt On India's .pdf
Nanandann Nilekani's ppt On India's .pdfNanandann Nilekani's ppt On India's .pdf
Nanandann Nilekani's ppt On India's .pdf
eddie19851
 
一比一原版(Deakin毕业证书)迪肯大学毕业证如何办理
一比一原版(Deakin毕业证书)迪肯大学毕业证如何办理一比一原版(Deakin毕业证书)迪肯大学毕业证如何办理
一比一原版(Deakin毕业证书)迪肯大学毕业证如何办理
oz8q3jxlp
 

Recently uploaded (20)

Malana- Gimlet Market Analysis (Portfolio 2)
Malana- Gimlet Market Analysis (Portfolio 2)Malana- Gimlet Market Analysis (Portfolio 2)
Malana- Gimlet Market Analysis (Portfolio 2)
 
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
一比一原版(UCSF文凭证书)旧金山分校毕业证如何办理
 
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
一比一原版(UofS毕业证书)萨省大学毕业证如何办理一比一原版(UofS毕业证书)萨省大学毕业证如何办理
一比一原版(UofS毕业证书)萨省大学毕业证如何办理
 
My burning issue is homelessness K.C.M.O.
My burning issue is homelessness K.C.M.O.My burning issue is homelessness K.C.M.O.
My burning issue is homelessness K.C.M.O.
 
一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理
一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理
一比一原版(BCU毕业证书)伯明翰城市大学毕业证如何办理
 
The affect of service quality and online reviews on customer loyalty in the E...
The affect of service quality and online reviews on customer loyalty in the E...The affect of service quality and online reviews on customer loyalty in the E...
The affect of service quality and online reviews on customer loyalty in the E...
 
一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理
一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理
一比一原版(爱大毕业证书)爱丁堡大学毕业证如何办理
 
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
一比一原版(UCSB文凭证书)圣芭芭拉分校毕业证如何办理
 
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
一比一原版(GWU,GW文凭证书)乔治·华盛顿大学毕业证如何办理
 
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Dat...
 
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
一比一原版(UniSA毕业证书)南澳大学毕业证如何办理
 
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...
 
Learn SQL from basic queries to Advance queries
Learn SQL from basic queries to Advance queriesLearn SQL from basic queries to Advance queries
Learn SQL from basic queries to Advance queries
 
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
一比一原版(Adelaide毕业证书)阿德莱德大学毕业证如何办理
 
Intelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicineIntelligence supported media monitoring in veterinary medicine
Intelligence supported media monitoring in veterinary medicine
 
The Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series DatabaseThe Building Blocks of QuestDB, a Time Series Database
The Building Blocks of QuestDB, a Time Series Database
 
Influence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business PlanInfluence of Marketing Strategy and Market Competition on Business Plan
Influence of Marketing Strategy and Market Competition on Business Plan
 
一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理
一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理
一比一原版(Bradford毕业证书)布拉德福德大学毕业证如何办理
 
Nanandann Nilekani's ppt On India's .pdf
Nanandann Nilekani's ppt On India's .pdfNanandann Nilekani's ppt On India's .pdf
Nanandann Nilekani's ppt On India's .pdf
 
一比一原版(Deakin毕业证书)迪肯大学毕业证如何办理
一比一原版(Deakin毕业证书)迪肯大学毕业证如何办理一比一原版(Deakin毕业证书)迪肯大学毕业证如何办理
一比一原版(Deakin毕业证书)迪肯大学毕业证如何办理
 

How to prepare for data science interviews

  • 1. Jianqiang (Jay) Wang Feb 21, 2015 Preparing for Technical Interview
  • 2. About me B.S. degree in Management Science and Ph.D. in Statistics Data scientist in twitter ads-ranking HP Labs : pricing & portfolio management, marketing, USDA : yield forecasting with satellite & survey data Instructor at Colorado State University Innovations in the intersection of statistics, computer science and business Applications in online advertising and e-commerce.
  • 3. Interview experiences: Google, LinkedIn, Apple, FB, twitter; startup positions; Phone screening (whiteboard coding, experiences, technical problems at high level) Business insights Algorithm design Analytics questions Statistics : concepts and methods Technical skills : SQL/R/Hadoop Interview experiences
  • 4. Business insight questions Think of ways of monetizing on WhatsApp? Propose a new Yelp feature? How to grow twitter monthly active users (MAU)? Recent news about the company & competitors Sign up and use their core products Keep informed of news in your interested industry
  • 5. Analytical questions Hypothetical problem to analyze & reason Define metrics Hypothesize possible reasons Estimate effects of various factors Suppose pinterest wants to associate a price tag with each pin, how to evaluate whether this works?
  • 6. Analytical : think like a data scientist What are possible causes that average time spent per user drops after this launch? How do you find out the root cause(s)? Finding pattern in data Tease out signals from noise Hypothesis testing Time series analysis Estimate the effects of various factors Regression A/B testing Computer simulation
  • 7. Statistics : concepts Mean, median, mode, quantile. Variance, range, IQR, covariance, correlation. p-value, likelihood function. How do you explain confidence interval to an engineer? What’s Bayes theorem? Examples? Gender-disease example. Microsoft bing example: better new algorithm .1%, test significant 5% of time under H0, and 20% of time under alternative.
  • 8. Statistics : methods Show the same twitter ads to 2,000 users, and 15 users clicked, CTR? What is multi-colinearity? What’s the difference between stratified & cluster sampling? Completely randomized block design? Give an example? Signup completion on FB. Book : statistical sleuth. Coursera statistics classes.
  • 9. Brain teaser Suppose you are given an unfair coin, how can you get probability of ½? Put 50 black balls and 50 white balls into 2 buckets. Randomly select a bucket and then a ball in the bucket. How to maximize the prob of choosing black? Given a fair die with 6 faces, how do you randomly generate numbers between 1 and 12? Programming: Rand6() -> Rand12().
  • 10. Whiteboard coding (DS) Suppose the amount we charge on ad clicks comes in a stream. Write a program to calculate cumulative cost. Correlation : (per ad cost, size of display)? Write a program to simulate M:F ratio assuming each family stops giving birth after the first boy (no twins). CS coding & algorithm complexity: given an array of numbers, find two that the sum is closest to 0? Leetcode & cracking the coding interview Practice with paper & pencil!
  • 11. Data manipulations Excel SQL Scripting language like R or python. Dataset with (gender, age, time spent on FB per day) Create age buckets: (0, 10], (10, 20], ... Average time spent for each (gender, age bucket). Table joins: inner join, left/right join, outer join (SQL & R)
  • 12. Resources Books Statistical sleuth Big data governance (quality, privacy, application in various verticals) Data just right (DS) the Startup of you 7 habits of highly effective people Quora post : how to become a data scientist Coursera classes Intro to statistics R programming Machine learning Intro to data science Web intelligence and big data (DS) glassdoor, careercup,...
  • 13. Crawl twitter data in R (or python) user info user tweets user network Search results; Text analytics (+ optional : predictive task) Frequency of n-grams Remove trivial words Find associated entities Visualization Associative words Sentiment Volume Interactive app : specify time window or specify entity, display raw tweets, show volume by time Twitter data analytics
  • 14. Projects Linkedin data; Twitter data: targeting people who wants to buy air tickets;