First we, have to understand what data scientists do. A data scientist use programming languages either R or python to uncover insights hidden in data, create data-drive products and also make predictions.
Why a data scientist?
You will work in rewarding ad intellectually challenging environment.
The demand for data scientists is projected to grow greatly within the next 10 years with the US bureau of statistics predicting that the demand will grow by 35% between 2022-2032.
Qualifications?
There are usually no set qualifications but it is recommended that you possess strong mathematical skills in order to understand and work with complex data. You should also be capable of using statistical software and in addition to being familiar with R or Python.
Roadmap
- Understand the role of a data scientist: Take your time to understand what a data scientist does. There are many blogs on the same and you can easily access them by googling.
- Explore job requirements: Look at what employers are looking for in a data scientist
- Get comfortable with math and statistics: Math and statistics are essential skills for data scientists
- Learn programming languages: Learn programming languages such as Python, R, and SQL
- Build basic skills: Build basic skills such as problem-solving, database management, and data wrangling
- Get familiar with data analytics tools: Learn how to use tools such as Tableau, Power BI, and Matplotlib
- Learn machine learning: Learn machine learning libraries such as TensorFlow, Keras, and Scikit-learn
- Develop your skillset: Pursue volunteer, open-source, or freelance projects to build your portfolio
- Build your network: Network with other data scientists and attend industry events
- Consider a data science internship: Gain practical experience through internships
- Polish your resume and start applying: Once you have the necessary skills and experience, start applying for data scientist positions.
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