Data Science and Data Scientist Requirements
Data science uses the most powerful hardware, programming systems, and most efficient algorithms to solve the data related problems.
Greetings.
I am a machine learning engineer based in India, possessing a sustained interest in machine learning since my undergraduate studies. I have completed Stanford University's machine learning course (Andrew Ng) via Coursera, and IBM's machine learning and deep learning curriculum. My current focus is on machine learning and data science projects, aiming to leverage my expertise for impactful, real-world problem-solving.
What is Data Science?
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data and apply knowledge from data across a broad range of application domains.
In the other words, we describe a data science is all about:
- Modeling the data using various complex and efficient algorithms
- Visualizing the data to get a better perspective
- Asking the correct questions and analyzing the raw data
- Understanding the data to make better decisions and finding the final result
Data Scientist Requirements
There is a describe in 4 components.
- Math & Statistics
- Domain Knowledge & Soft Skills
- Programming & Database
- Communication & Visualization
1. MATH and STATISTICS
- Machine Learning
- Deep Learning
- Statistical Modeling
- Experiment Design
- Bayesian Interface
- Supervised Learning :
- Decision Trees
- Random Forests
- Logistic Regression
- Linear Regression
- Unsupervised Learning :
- Clustering
- Dimensionally Reduction
- Optimization :
- Gradient Descent
- Variants
2. DOMAIN KNOWLEDGE and SOFT SKILLS
- Passionate about the Business
- Curious about Data
- Influence without Authority
- Problem Solver
- Strategic
- Proactive
- Creative
- Innovative
- Collaborative
3. PROGRAMMING and DATABASE
- Computer Science Fundamentals
- Python / R
- Databases SQL and NoSQL
- Relational Algebra
- Parallel Databases
- Parallel Query Processing
- MapReduce Concepts
- Hadoop and Hive/Pig
- Custom Reducers
- Experience with xaaS like AWS
4. COMMUNICATION and VISUALIZATION
- Able to engage with seniors
- Translate data-driven insights into decision and actions
- Visual art design
- R packages like ggplot or lattice
- Knowledge of any of Visualization tools
- Flare
- D3.js
- Tableau
