A data scientist can be expected to accomplish the following tasks:
- data mining or extraction of usable data
- using machine learning tools to select features, create and optimize classifiers
- enhancing data collection procedures
- preprocessing of structured and unstructured data
- data processing, cleansing and validating
- analyzing data in order to find patterns
- working together with experts of both IT and business, and understanding the problems and needs of both fields.
- developing prediction systems and machine learning algorithms
Projects need the expertise of a data scientist in the following cases:
- they incorporate tasks that require one to manage huge amount of data and solve complex issues
- they value data, the aim of the project is to get valuable information out of a massive amount of data, which is often unstructured as well
- they seek novel and creative solutions
Important data science tools:
- Bookdown
- Feature Labs
- Flask
- RStudio
- Dataflow
- Keras
- RapidMiner
- Python
- Hadoop
- Tableau
- AWS Lambda
- Panda
- Apache Giraph
- Power BI
- DataRobot
- MySQL
Our Text Analytics Solutions are gathered in the TAS Platform.