According to Glassdoor, Data Scientist is one of the best professions in Europe. You will be more surprised to hear that the average paid salary is €72,000. However, the demand for data scientists is not saturated yet, with approximate 769,000 unfilled positions in this particular field in Europe by 2020.
Due to increase in demand, choosing this field can lead you to an enticing career. Those who are not a data scientist but are keen to become and have an exceptional interest with data, often ask:
What Things Do I Need To Know Before Starting as A Data Scientist?
If you are planning to switch your career to data science, this is the best time as 2019 will offer plenty of rewarding chances. The point of this article is to make it clear about the skills and practices required before turning into a data scientist.
1. Technical Skills – The Most Important
The most critical technical skills required for a data scientist are:
Computing frameworks and examining facts
Structuring data from the bulk of information.
This implies that you should have a good grip at math, programming, and statistics. One method for consenting to the essential is to have a relevant educational background.
Data scientists are usually Ph.D. and Masters in computer science, engineering or statistics. It enables them to build a stronger foundation so they can connect to the technical aspects in the designated field or a particular task.
Let’s have a brief look at some skills which you will need to learn.
a. Programming: You are required to learn some essential coding languages which help you organize and analyze the sets of data provided to you in various forms. There are numerous programming languages preferred in this field. Perl is the most common among others. However, people love to use C/C++, SQL, and Java as well.
b. A Grip at Analytical Tools: To extract the valuable insight from the organized and analyzed data, the knowledge of analytical tools is compulsory. Along with SAS, tools like R, Hadoop, Spark, and Hive are the most common data scrutiny tools. Scientists recommend doing online certification courses as well which will help you more to enhance your expertise.
c. Machine Learning and Artificial Intelligence: In a survey, Kaggle revealed that only a small percentage of data scientists are equipped with advanced machine learning skills. These skills which every data professional should be competent with are:
Supervised and Unsupervised ML
Reinforcement and Adversarial Learning
Natural Language Processing
If you need to be proficient and prominent amongst the other professional, you will need to cope with these skills. It will provide you with a helping hand while solving the numerous data science problems based on predictions.
2. Non-Technical Skills To Be A Great Professional
Only technical abilities, educational qualities, and certificates will not cherish your career. As a data scientist, some non-technical skills could enhance your value in the industry.
a. Strong Communication Skills: There is no doubt, as a data scientist you would have the best understanding of the data. But, within an organization what matters is how best you can deliver your opinion and ideology to others especially the non-technical ones. Moreover, everyone from any business needs to communicate internally and externally through emails and other mediums. With the proofreading & writings skills, tools such as CrowdWriter and Grammarly can help you to produce a mistake-free report.
Not only it will help to communicate with others but will let you present the data more effectively. Storytelling around your data is essential as it makes the data easy to understand for everyone. Presenting a set of data using tables and graphs could not be too much interactive. You need to take assistance from storytelling skills. Through this way, the insight of data you share will help to convey your findings with the employees appropriately.
b. Business Awareness: You, as a data professional are required to have a clear insight and intuitive eye over business and factors that build up a successful business model. All the technical skills won’t be productive at all if you are not blessed with business acumen.
With the particular ability, you will be able to tackle the issues that are mandatory for the growth and sustainability of an organization. Moreover, you can explore more trading opportunities for your company.
c. Teamwork: You cannot work alone. You need a team for achieving a target. You are supposed to develop strategies with company executives, designers, and product managers for better results. Often you will need to plan with marketing managers to launch the campaigns that convert. To create a data pipelines and enhance the workflow you deal with software developers and clients as well.
Moreover, you must be in collaboration with your teammates for developing use cases so that you can know the business goals and what data is required to solve the issues. Literally, you will be working with each and every organization’s member, along with your customers.
Data scientists are highly educated professionals. About 75% of them are Ph.D. or Masters. However, you are not required to be graduated from a reputed university. 25% of data scientist has graduated from an ‘unranked university’.
Let me make it more convenient for you. Most of the data scientists have degrees in Computer Science, Statistics, Mathematics, Engineering or Social Sciences. Only 13% of them have attended a data science and analysis university program. What you all need is a quantitative background, and you have a variety to choose in that department as well.
So, there is no need to jump into extra academic programs to cope with the required skills. There are numerous online courses which can help you with the purpose of enhancing your capabilities. About 40% of data scientist enrolls themselves in online courses.
Useful Tip and Helpful Resources
Data science is not an easy job to handle. You must be eager to learn new things daily. Your behaviour decides that the path you have chosen will lead you to success or not. You are required to develop a learning attitude.
Albert Einstein said, "I have no special talent. I am only passionately curious."
You need to be asking questions and raising issues about your data because you will be spending about 80% of your time analyzing data. Without being passionate about your profession, you will not be able to grow your career.
To define the right path to your career you can:
Participate in competitions on Kaggle such as The Titanic Competition or House Price Prediction. It will motivate you and raise your prediction level.
Join the relevant community and share your insights with others.
Create a structure for your learning. As a beginner, you can start with some free stuff like:
Analytics Vidhya data science learning path
Keep in mind that this is the right time, to begin with your career, stay focused, and you will achieve it.
Amanda Jerelyn is an independent woman who recently graduated from the University of London. She is a career counsellor and also working part-time as a marketing tutor at Academist Help. Amanda has a keen interest in technological advancement, and she is fond of travelling.