Data Scientist Skills: Essential programming skills to leverage large amounts of data
Published
The skills of a data scientist require undivided attention as there are many complex problems you need to solve. Data scientists review data and statistics and use computer algorithms to answer questions that help improve a business.
Unlike data analysts, data scientists do more than just identify trends. They try to help companies by predicting future results. However, to accomplish this task, you need to master the skills of a data scientist.
In this guide, we'll go over all the soft skills and technical skills a data scientist needs to best perform their job.
If you want to acquire new data science skills or expand your existing skills, Skillshare is for you. Please click here to access Skillshare's learning platform and gain new insights into a wide variety of topics.
What is a data scientist and what are his tasks?
Data scientists design processes to create complex algorithms and models that analyze data. The day-to-day tasks of a data scientist include:
- Creation of data visualizations
- Development of forecast models
- Use of programming languages such as Python, R, SQL and Tableau
- Creating and testing algorithms
- Retrieve, merge and analyze data
- Use of machine learning
- Analyzing Big Data
Soft skills for data scientists
In a field like data science, soft skills are crucial because the work can be complicated. These soft skills prepare a data scientist for their work and also help them develop technical skills. The most important soft skills include:
Critical thinking
This is an important skill because data scientists deal with complex problems and need to be able to look at things from all angles. A data scientist must analyze large amounts of information to achieve the results desired by his employer.
Business knowledge
A data scientist should have general business knowledge as they will use their expertise to influence business decisions. They should be very familiar with the company they work for and its current developments.
Communication
Since a data scientist works with complex algorithms, he or she must have solid communication skills to accurately convey information to management. If necessary, they must convey information in a non-technical way so that employees understand what the data means for the company.
Troubleshooting
In data science, problem solving is an important part of the job. Any problems in the algorithms or software need to be corrected, so data scientists must have proactive problem-solving skills.
Technical skills for data scientists
Like soft skills, technical skills are also an important part of data science. These technical skills demonstrate your experience and knowledge of data, algorithms, software and programming. Below are some technical skills every data scientist should master.
- programming
- Cloud Computing
- Data processing
- Knowledge of data visualization tools
- Knowledge of data query languages
- Programming languages like Python, R, SQL, Tableau
- Knowledge of AI and machine learning
- Good mathematical knowledge in statistics, calculus and linear algebra
- Software development
- Intuition for data
- Knowledge of Apache Spark
Difference between a data scientist and a data analyst
Data scientists are responsible for solving a company's problems. They provide data visualizations and explain how a company can use the data collected to improve. This includes reviewing past and current data to predict future business results.
Data analysts are responsible for analyzing current data to assess a company's performance. They identify trends and patterns and interpret and analyze data to create charts and graphs that provide insights to the business.
Data Scientist Jobs
A data scientist can work in many areas. According to the Bureau of Labor Statistics, data scientists in the United States earn an average of $100,560 per year.
Someone who wants to enter the field of data science can work as:
- Data Scientist
- Data engineer
- Data architect
- Data and Analytics Manager
- Data mining specialist
- Machine learning engineer
- Database developer
- Business-Analyst
- Database Administrator
- Computer programming
Skills for your data scientist resume
If you are looking for a job as a data scientist, you should design your resume to showcase your experience and skills. Your employer needs to see these skills so they know how much experience you have. Below are some skills to include on your data scientist resume.
- Programming languages such as R, SQL and Python
- Data visualization
- Grit and version control
- Data manipulation
- Data Cleansing
- Data entry
- Statistics
- APIs
- Machine learning
The more experience you gain, the more marketable you become. You can gain relevant skills through internships, an entry-level job, taking an online course, or a hands-on learning lab. These experiences are important for employers to identify which candidate is the best fit for their company.
Conclusion: Do you have the skills to become a data scientist?
You need many skills to become a data scientist. In the field of data science, you will manage data, write code in various programming languages, solve mathematical problems, and find solutions that help companies improve. These skills are crucial to becoming a professional data scientist.
If you are interested in starting a career as a data scientist, you should make sure you know all the necessary skills so that you can quickly find career opportunities in the data science field.
