Data Science

Job Roles in Data Science Field

Data Analyst/Business Analyst
- Pulling data out of SQL databases, becoming an Excel or Tableu master, and producing basic data visualizations and reporting dashboards. Occasionally analyze the results of an A/B test or take the lead on your company’s Google Analytics account. Data warehousing.
- Understand the business need and present the data science solution to clients
Data Engineer/Data Management Professional/Hadoop
- Hired by companies who start seeing a lot of traffic [and increasingly large amounts of data], and they need someone to set up a lot of data infrastructure. Heavy statistics and machine learning expertise is less important than strong software engineering skills.
Machine Learning Engineer
- Ideal for someone who has a formal mathematics, statistics or physics background and is hoping to continue down a more academic path. Companies that fall into this group could be consumer facing companies with massive amounts of data or companies that are offering data-based service.
- Algorithms, predictive analytics and deep learning
Data Scientist
- Perform analysis, touch production code, visualize data, etc.
- Familiarity with tools designed for ‘big data’ and experience with messy real-life datasets
- Do anything and everything related to data

12 Steps of Predictive Modeling

Understanding the problem and business objective
Finding why machine learning is needed to solve the problem and what are the methods in literature
Selecting a single number metric
Doing exploratory data analysis
Pre-processing the data
- Data cleansing
- Outlier removal
- Normalization / Standardization - Dummy variable creation
Feature engineering
- Feature selection
- Feature transformation
- Variable interaction
- Feature creation
Selecting the modeling algorithm (from simple to complex)
Parameter tuning through cross validation
Building the model
Ensembling of models
Checking the results on un-seen data and iterate
Deploy model

Flowchart to Become a Data Scientist