Data Scientists are playing an increasingly vital role in corporations all over the world. They use a range of techniques and applications to provide their employers with crucial information regarding customers, buying patterns, product awareness and pathways to market. The data they acquire can influence company policies both now and many years into the future.
Duties and responsibilities - What does a Data Scientist do?
Duties that come under the auspices of a Data Scientist include:
- Researching organisations and industry sectors to improve processes and systems
- Collecting data that will benefit the employer, and communicating which sections of data are important
- Filtering out unwanted information, using data cleansing techniques
- Developing algorithms to assist with data searches and streamlining future searches
- Organising data and communicating information to senior management, including highlighting patterns of relevant information
- Presenting conclusions and recommending actions, to both senior management and potentially to affected departments
Qualities needed for a successful Data Scientist
The role of a Data Scientist is a highly technical one, often requiring a strong academic background allied to extensive experience in a particular field. They will have a natural intellectual curiosity along with a penchant for solving problems. Strong levels of business acumen will be an advantage, as well as the ability to perform equally well when working alone and as part of a team.
Effective communication skills are important, too, especially when there is a need to interpret information to those with a less technical understanding of processes and systems. Experience in this role is always beneficial, even more so if the candidate has a strong understanding of a specific sector of industry. Business knowledge, especially in global business, will be a major advantage for a candidate.
Qualifications and technical skills - How to become a Data Scientist?
Formal qualifications are often a must-have. The majority of Data Scientists in the corporate world have a master's degrees at the very least, and many have passed PhD exams as well. There are several subject specialities that potential employers will be looking for, including computer science, mathematics, physical and social sciences, statistics, engineering, operational research, machine learning and data science.
Various technical requirements may be needed by potential employers. Some of the most in demand are a sound knowledge of R programming, Python coding, Hadoop platform, Apache Spark SQL/noSQL databases and ETL processes. Using data visualisation software such as Tableau, Power BI, Looker, D3 and Jupyter notebooks to communicate and interpret that information can be of vital importance.
Career development - What is the next step after Data Scientist?
Newcomers to this role often come directly from universities or from internships and placements. Experienced Data Scientists can also easily transfer their skills and knowledge from sector to sector, providing an opportunity to build a rewarding career path along the way.
There are a wide range sectors of industry in which Data Scientists can work, such as financial, health, retail, IT, governance, e-commerce, engineering, maritime, aviation, logistics and more. Future development roles include that of Senior Data Scientist and in specialisations such as artificial intelligence, machine learning, unstructured data, and data visualisation.
Salary and remuneration - How much does a Data Scientist make?
Salary levels for Data Scientists will often be viewed in relation to the value they offer to the company. Senior roles are highly rewarding financially, and usually include an impressive benefits package.