A data scientist is a person who extracts raw data, processes it, and creates new data products.
Such data scientists are expected to be experts in data analytics technologies, including data management, data mining, statistical analysis, programming languages (e.g., Python or R), machine learning, deep learning, predictive modeling, etc.
Below are some important tips to remember when creating your data science resume.
When creating a data science resume, it is important to keep it as brief as possible.
A data science resume should be about 1 page long since data scientists are likely to have many other skills unrelated to data science.
Including too much content on your data science resume will make it difficult for hiring managers to quickly scan through all the information.
When creating a data science resume, it is important to customize each resume for each job application.
This means tailoring the data science sections of your data science resume for each position and company that you're applying to.
For example, if you're applying for a data analyst role, you may want to focus more on data coding and data mining than data science.
If you're applying for a data scientist role, it may be better to focus on data cleansing and data visualization instead of data coding and data mining.
It's important that you keep your data science resume updated with all your latest projects and skills.
The data science resume objective statement should be at the top of your data science resume.
This serves as a summary of what you want to do and where you see yourself in the data science industry.
For example, a data scientist's data science resume objective statement maybe "I am passionate about finding insights within data to help companies make data-driven business decisions."
Stay Positive and Highlight the Good Points.
As with any data scientist resume, you should highlight your data science background.
Know what data scientists are expected to know, understand what skills data scientists possess.
This will help you summarize them into actionable statements that you can include in your data science resume.
Add your professional qualification data science data scientists should have, such as data management, data analysis, and data mining.
List these data science qualifications at the top of your data scienceresume just below the objective statement.
This will help to establish credibility with hiring managers and show them that you're serious about making a career change or advancing in your data science field.
while creating your data science resume, add additional skills, both hard and soft skills.
For example, a data science resume can contain data management, data mining, statistical analysis, programming languages (e.g., Python or R), machine learning, deep learning, predictive modeling, etc. data scientists may have other skills too, like data visualization excel data processing, big data, etc.
Proficient in PHP, Ruby on Rails, Java, C++, and Python
Experienced at managing relational and non-relational database software such as MySQL, SQLite3, Mongo DB, and JSON
Technical leadership and training data management activities such as collection, cleansing, standardization, and mining.
