1. D ATA S CIENTISTS Who are they and what do they do?

2. W HO DO Y OU T HINK W E A RE ? What my friends think I doWhat my mom thinks I do What society thinks I do What my boss thinks I doWhat I think I doWhat I really do

3. W HAT B UZZ IS A ROUND ?

4. “Data Scientist is an statistician who lives in California.” “Data Scientist is an statistics on Mac.” “A data scientist is someone who's is better at statistics than any developer and better at development than any statistician” worse statistician worse developer “A data scientist is someone who's is better at statistics than any developer and better at development than any statistician”

5. “I keep saying that the sexy job in the next 10 years will be statisticians. And I’m not kidding.” − Chief Economist, Google http://goo.gl/jsnUI

6. “Data Scientist: The Sexiest Job of the 21st Century. New key player in organizations is the “data scientist.” It’s a high-ranking professional with the training and curiosity to make discoveries in the world of big data” − Harvard Business School http://goo.gl/rDDIT

7. W HAT S KILLS ARE N ECESSARY ? StatisticsMathVisualization High Performance Computing Computer Vision Machine Learning Data Engineering Data Warehousing Data Science Domain Expertise

8. W HAT O PPORTUNITIES W E O FFER ? Recommendation Systems Targeted Advertisement Market Segmentation Fraud Detection Customer Behavior Analysis Stock Price Forecasting

9. W HAT T ASKS W E S OLVE ? Regression Classification Similarity matching Clustering Behavior Description Among all the our customers, which are likely to respond to a given offer? What is the chance that the new contract will be signed? How much will a given customer use the service? How much money can we earn selling the service? What items are commonly purchased together? Do our customers form natural groups or segments? What is the typical cell phone usage of this customer segment? Among all user transactions, which are likely be marked as fraud? Link Prediction What items could be recommended for user, based on his previous purchases? What are the companies similar to our best business customers?

10. W HAT T OOLS DO W E U SE Big Data Technologies Programming Languages IDEs and Libraries Visualization Enterprise Software Python, R, Java (bonus Clojure, Haskell, Scala) Hadoop, HDFS & MapReduce... (bonus: Spark, Storm) D3.js, Gephi, ggplot2, Tableau SPSS, MatLab, SAS ( the enterprise man) NoSQLMongoDB, Couchbase, Cassandra, HBase Knime, Weka, RapidMiner, SciPy, NumPy, scikit-learn, MS Excel: The most used and most understood DS tool

11. B USINESS A NALYTICS Descriptive Analytics Predictive Analytics Prescriptive Analytics What happened? What is happening? Business reporting Dashboards Scorecards Data warehousing Well defined business problems and opportunities What will happen? Why will it happen? What should I do? Why should I do it? Data Mining Text Mining Web Mining Forecasting Optimization Simulation Decision Modeling Expert Systems Accurate projections of the future states and conditions Best possible business decisions and transactions Questions Enablers Outcomes

12. C OMMON SDLC WILL NOT F IT H ERE Business Understanding Data Data Understanding Data Preparation Modeling Evaluation Deployment

13. T HE R OAD IS NOT E ASY

14. Q UESTIONS ?