If you want to get a job in the field of Data Science, you need to follow this path:
Starting out: Learn a programming language that you will be comfortable with. The most commonly used programming languages in Data Science are Python and R language.
Learning Mathematics: This is critical, since, as a Data Scientist, you will be working with raw data. Having a strong hold on Mathematics and Statistics will be helpful. You need to pay special attention to Descriptive statistics, Probability, Inferential Statistics to further your knowledge.
Understanding Libraries: This is important to perform tasks like data processing and for structured data plotting. Some of the most common libraries are SciPy, ggplot, Matplotlib and others.
Understanding Data visualization: Another important aspect of a Data Scientist job is to find patterns in unstructured data and to communicate the same to people who are from non-technical backgrounds. Therefore, data visualization becomes important. The libraries used for this task are ggplot2 and matplotlib.
Understanding data pre-processing: The unstructured nature of data makes it important for data scientists to pre-process the data before making it ready for analysis. This is usually done through feature engineering and variable selection.
Machine Learning and Deep Learning: Deep learning algorithms are used while dealing with a huge set of data. You need to have a tight grasp on topics like CNN, RNN, Neural networks, etc.
Learning Natural Language processing: This is important to understand how the text form of data can be processed and classified.