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73 Examples of Data Science Skills

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Data science is the use of mathematics, statistical methods, machine learning, algorithms and systems to develop meaning and actionable information from data. This generally requires a background in a quantitative discipline such as statistics, mathematics, physics or computer science. Data science skills include working knowledge of methods, processes, algorithms, platforms, languages and techniques that are used to build models and explore data. Soft skills such as communication, public speaking and stakeholder management are also important to data science roles. The following are common data science skills.
Algorithms
Analytics
Backtesting
Big Data Platforms
Business Analysis
Business Intelligence
Calculus
Cloud Platforms
Coding
Cohort Analysis
Data Aggregation
Data Analysis
Data Architecture
Data Classification
Data Cleaning
Data Communication
Data Exploration
Data Flows
Data Harmonization
Data Historians
Data Ingestion
Data Integration
Data Intuition
Data Lineage
Data Management
Data Mining
Data Models
Data Visualization
Data Wrangling
Databases
Decision Modeling
Decision Trees
Deep Learning
Deployment
Distributed Processing of Large Datasets
Ensemble Methods
Executive Communication
Experiment Design
Extract
Forecasting
Information Security
Interdisciplinary Learning
Linear Algebra
Linear Models
Machine Learning
Markov Chain Monte Carlo (MCMC)
Monitoring Model Performance
Multivariate Analysis
Neural Networks
Predictive Analytics
Prescriptive Analytics
Presentations
Probability Distributions
Problem Framing
Product Development
Public Speaking
Random Forests
Regression Analysis
Requirements Gathering
SQL
Sampling Methods
Scripting
Stakeholder Management
Statistical Hypothesis Testing
Statistical Learning
Statistical Software
Statistics
Statistics Platforms
Stochastic Models
Structured Thinking
Testing
Transform & Load (ETL)
Trend Analysis

Data Science Skills

This is the complete list of articles we have written about data science skills.
Algorithms
Analytics
Backtesting
Business Analysis
Coding
Cohort Analysis
Data Analysis
Data Architecture
Data Integration
Data Lineage
Data Management
Data Mining
Data Wrangling
Databases
Decision Trees
Deep Learning
Experiment Design
Forecasting
Information Security
Predictive Analytics
Problem Framing
Product Development
Public Speaking
Regression Analysis
Statistics
Testing
More ...
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