Life of a data scientist (pub)
6 likes6,836 views
The document discusses the role and responsibilities of a data scientist. It describes how data scientists take large amounts of messy data and use skills in math, statistics, and programming to organize and analyze the data to uncover solutions to business problems. An effective data scientist has strong skills in both statistics and software engineering. The document also outlines the scientific process that data scientists follow, including developing algorithms and models, testing hypotheses on data, deploying solutions, and continuously monitoring and improving based on results.
![DB
Log
SQL
Data
TXT / EXL
Visualization
Implement
Test & Deploy
[KR]
Algorithm
- Regression
- Classification
- Clustering
[Insight]](https://image.slidesharecdn.com/lifeofadatascientistpub-160607063101/85/Life-of-a-data-scientist-pub-10-320.jpg)
![DB
Log
SQL Data
Implement
Test & Deploy
[KR]
Algorithm
- Regression
- Classification
- Clustering
[Insight]
20 60
15
5](https://image.slidesharecdn.com/lifeofadatascientistpub-160607063101/85/Life-of-a-data-scientist-pub-35-320.jpg)
Life of a data scientist (pub)
- 1. Life of Data Scientist myths and reality Jeong, Buhwan Ph.D Data Hacker / Kakao Corp.
- 2. Data scientists are big data wranglers. They take an enormous mass of messy data points and use their formidable skills in math, statistics and programming to clean, massage and organize them. Then they apply all their analytic powers and domain knowledge to uncover hidden solutions to business challenges. Script (modified) from http://www.mastersindatascience.org/careers/data-scientist/
- 3. A data scientist is someone who is better at statistics than any software engineer and better at software engineering than any statistician. domain knowledge business understanding+ http://www.mastersindatascience.org/careers/data-scientist/
- 10. DB Log SQL Data TXT / EXL Visualization Implement Test & Deploy [KR] Algorithm - Regression - Classification - Clustering [Insight]
- 11. Big Data?
- 13. Value BIG & FAST SMART Count & Trend Predictive Technical Meaningful Analytics Volume Variety Velocity Engineering Science
- 14. Data Science Scientific Method Proved by Theory Verified with Experiment Algorithm (Equations) Testing (Evidence)
- 19. Test Deploy Modeling Test set Observe A (Treatment) B (Control) ← Offline : Online → Solve
- 20. M T W T F S S Code Release Off-line Test On-line Test Deployment Monitoring & Improvement Netflix’s Weekly Test & Deployment
- 23. From Yahoo! (Creative Best Practices: Native Ads)
- 24. From Yahoo! (Creative Best Practices: Native Ads)
- 26. A/B Test Configuration Traffic-driven For every incoming request, if random() < 0.1, then assign the treatment group (10%) otherwise, assign the control group (90%) User-driven For every requestor (whose userId ends with ‘NN’) if ‘NN’ is in ’00 ~ 09’, then assign the treatment group otherwise, assign the control group
- 27. Random Control Group Treatment (A) A/B Test Random Control Group Treatment A Treatment B Treatment C Multivariate Test
- 32. Red Daum vs Blue Daum
- 35. DB Log SQL Data Implement Test & Deploy [KR] Algorithm - Regression - Classification - Clustering [Insight] 20 60 15 5
- 37. Hacking Data for business goals - Right data - Right algorithm - Right evaluation
- 38. Good UI/UX is defined by User Adoption
- 39. Human Hacker Image from https://goo.gl/vClux5
- 40. Enjoy your Jeju