A data scientist is a professional who uses data to interpret and predict insights that can help organisations make better decisions. This profession is one of the fastest-growing occupations in the world currently as data scientists can help develop anything, starting from the development of self-drive cars, automatically captioning your images, and avoiding security threats. Data scientists work closely with business stakeholders or organisations to understand their business goals and help them achieve them. In today’s world, it’s very easy to gather data that require various data-processing methods which is where data scientists come in.
As the demand for data scientists grows, this discipline sounds like a favorable career option for students and graduates that are offered competing salaries. To start your journey as a data scientist, it’s important to enroll in a data science course that can teach you all about python, statistics, predictive modeling, and other basic skills required.
Here are the steps for you to become a data scientist:
1. Get a degree
It’s important to have a minimum of a bachelor’s degree or data science background to show your employer that will help you secure the job. Graduating with a degree in computer science, statistics, and data science will definitely help you stand out from the crowd as data scientists need to work with complex algorithms every day. They process data and find ways to extract useful insights from them which may require a technical background.
2. Technical Skills
It’s important to learn programming languages like Python, R, SQL, and SAS and create graphs using Excel, Tableau, and PowerBI. You can also work on improving your machine-learning skills to help you extract information from data analytical tools like Adobe Spark, Hive, and Apache.
You can even go a step further by earning various certifications by enrolling in programs to showcase your knowledge in your resume.
3. Communication Skills
A data scientist grapples with unstructured data every day to provide necessary insights hence it’s vital for you to have good communication skills to successfully convey your findings to the team. You must be effective in helping others understand your data findings who may not have the same background.
With clear communication, you can help avoid any miscommunications and disruptions that may occur ensuring the team works well together.
4. Business Skills
You should be business savvy enough to predict the potential challenges that may come up in the future and be able to find ways to solve them. As much as data scientists collect data every day, they also need to have good business acumen in order to understand and provide what a business needs.
This job is not going to be as straightforward as you imagine.
You will need to be prepared to adapt and overcome hiccups that might occur while gathering large sets of data every day. It’s important to be adaptable and flexible when it comes to this career choice.
5. Entry-level data science job
You can start with an entry-level job like a business analyst or a data engineer and slowly work your way up to a scientist level with the required knowledge and experience.
What are some popular roles within Data Science?
The demand for data scientists keeps growing day by day.
People with the right background and necessary skills can find jobs in healthcare, finance, manufacturing, and many other industries.
1. Data Scientist
A data scientist’s responsibilities include grappling with data by using predictive modeling. This ensures they can correctly predict the business solutions required to increase customer satisfaction, revenue generated, and customer experience.
Data scientists have to work with various teams to monitor the outcomes and implement models.
2. Data Engineer
They build the system required for data extraction, data transformation, and data loading. They help in identifying and improving internal processes as well.
3. Machine Learning Engineer
Machine learning engineers are responsible for building AI software that can automate various processes seamlessly. They are involved in deep learning and help businesses predict and improve their business insights.
4. Data Administrator
They are responsible for structuring the new data and storing it, implementing security features to secure data, and updating the already existing databases in the system.
5. Data Architect
Data architects design and store data in databases, structure solutions for the business, research and design databases as required, and collect data using pipelines.
6. Data Analyst
They help in maintaining the databases in an organisation as they acquire data from various sources. Using this data, they study, analyse and come up with data collection systems and solutions that an organisation may require.
7. Business Analyst
Business Analysts use data to find out what a business lacks and present it to the decision makers that can help in the improvement of the said business. They use their knowledge to find out wasteful business practices and plan out cost-effective models.
Data science is reported to be an enjoyable career choice for professionals. Organisations and businesses today are grappling to keep up with a large amount of data that comes in every day hence data scientists are always in demand. With the proper motivation and hard work, you will surely excel in this career in no time.