Data science jobs are considered one of the hottest jobs in the industry. According to a Glassdoor report, data science professionals enjoy one of the highest salaries and have a satisfaction of 4.2 out of 5. Thus, it is one of the most sought-after professions in the IT industry. However, it could be very intimidating to embark on the path to becoming a data scientist.
Who is a Data Scientist?
A data scientist is a professional and expert in collecting, handling, analysing, and interpreting data. Top organisations consider them to be the top asset for their scope of growth and improvement. These professionals have the responsibility of developing customised algorithms and data models for applying to data sets. In this way, they take advantage of valuable information for problem-solving, forecasting, decision-making, and discovering trends. It is important for them to possess both technical and non-technical skills to excel in work. A deep understanding of programming, mathematics, statistics, communication, machine learning algorithms, and problem-solving skills is necessary for these professionals. You can consider taking a data analyst course from a trusted educational institute to gain these skills and abilities. In this blog, we are going to talk about the path to becoming a data scientist.
A Career in Data Science
A career in data science is personally rewarding and financially lucrative. However, becoming a skilled data scientist will take time, complete dedication, and effort.
Choose the Specific Path
Data Science itself is a very broad field with so many opportunities for career growth and success. Thus, if you are ready to start your journey, you have to first select the industry in which you will ultimately be working. Usually, data scientists play similar roles and duties across different industries. However, the specific kind of information to be analysed depends on your employer and industry. Although, data science is being used in various industries. We can still segregate data science into five major sectors: healthcare, finance, manufacturing, retail, and transportation. These industries are known for their needs of collecting massive amounts of data, analysing the data accurately to discover trends, and meaningful insights to help businesses in decision-making and optimise various processes.
Here are the prominent industries where there’s a huge demand for data scientists;
The retail industry expects professionals to have impeccable communication skills and analytical skills. Data scientists are expected to present their discoveries to business owners and consumers.
The data science professionals working in the healthcare industry need to know medicine and healthcare terminology. They also need to have expertise in the medical record management and spreadsheet analysis.
Data science professionals in the finance industry must have gained proficiency with Excel/spreadsheets and data collection from a variety of sources.
Data science professionals working in the manufacturing industry must have deep knowledge and experience with predictive analytics. This is due to the fact that they primarily determine when the manufacturing machines will require maintenance or repairs.
Data science experts working in the transportation sector must be exceptional in handling data visualisation and econometrics modelling.
Polish the Necessary Skills
Data scientists are highly skilled professionals; they have expertise in computer science and mathematics. You might need to revise your mathematical knowledge by studying some relevant topics. Thus, if you are planning to take a data science certificate course, it would be best to improve your grasp of applicable principles and practices before enrolling on the course.
The following are the mathematical skills that you need to brush up on to become a data scientist;
- Linear Algebra
- Discrete Math
Technical understanding of coding languages is also equally important as strong mathematical skills. You will need to gain experience with languages such as Java, Python, R, SQL, HTML, NoSQL, and more. There is some industry-standard software that data science professionals should master. Thus, learning Hadoop or Tableau could prove to be a huge advantage for data science aspirants.
In your journey to polishing the necessary skills, you will also need to work on soft skills such as communication, critical thinking, analytics, problem-solving, and more. You have to train yourself to discover the obstacles, find solutions, and convey the insights clearly and systematically.
Receive Formal Education
Getting some specialised education is important for a data scientist to excel in his/her field. It doesn’t matter how much you are already prepared with technical and mathematical skills. You must possess some industry-relevant skills and theoretical knowledge to get employed in a reputable. A data science certificate course could be the best academic path. You can also pursue a master degree in data science. Quality education could be the best way to open up to new opportunities and make yourself more employable in the competitive market.
Learn About the Entry-Level Role
Before you start searching for jobs, it would be better to learn what could be expected from an entry-level role. Different companies use data in different ways. Here, the data scientists are required to provide analysis for improving cost-effectiveness, financial performance, manage risk levels, build strategies, and assess a product or service. Thus, you must be very confident with what you will be doing and the abilities that you need to showcase your expertise when required.
The main duties and responsibilities in an entry-level data scientist job;
- Creating and managing studies related to data collection
- Developing tools for automating data collection
- Reformatting data for making analysis simpler
- Working with huge data sets for usable information
- Generating critical reports and presentations
Data scientists are responsible for providing critical services to companies, government agencies, and other organisations by processing and deriving insights from huge sets of data. Each business or organisation is meant to have different goals, priorities, and knowledge that should be understood in advance.
Boosting Your Chances of Getting Hired
There is a huge demand for data science professionals. However, the competition is also getting stiff, with more data scientists entering the market. Thus, you need the right skills to stand out from your competition.
A data science certificate course from the London School of Emerging Technology could be the best way to fast track your career in data science. It will give you a chance to learn from industry experts and gain practical experience with hands-on training. You will be job-ready from day one after completing the certificate course.
Professional Portfolio Development
A professional portfolio of your work is very important to showcase the quality of your experience. It is a very productive way to enter the industry. Having a good portfolio, you can overcome the lack of job experience and demonstrate your skills while entering the industry. A data science portfolio should highlight all of your projects and showcase your technical knowledge and skills. The main purpose of a portfolio is to show that you are ready for an entry-level data science profession.
How to process data?
thanks for info