Data science is an important job that essentially gathers and analyzes data toward the goal of solving problems for businesses. Crossing industries including healthcare, technology, finance, telecommunications, energy and many others.
But, despite the potential for this impressive career, many people remain unsure about what exactly the profession entails — and how people can join the field. What is a data scientist? Where do you find them? What do they do?
In this article, we lay out what the profession actually is, the responsibilities involved and the skills you need to pursue a career in the field — as well as your expected earnings.
While the precise responsibilities and nature of the job vary according to a variety of factors, ultimately, a data scientist seeks to make meaning out of the data she collects, organizes and analyzes, using it to meet the larger goals of the company. In addition to gathering data, she is also responsible for creating tools to facilitate the process, identifying what type of information she needs and how it can help solve problems, as well as performing statistical analysis on the information.
Based on their recommendations, businesses make decisions to achieve their objectives.
The role of a data scientist is often confused with that of a data analyst. While both collect and make meaning of data, a key difference is that data scientists also create models and processes for these purposes, often using advanced programming and coding skills. Data science also requires an advanced degree — usually a master’s and in some cases a PhD — while data analytics typically only requires a bachelor’s degree.
A data scientist's day-to-day tasks and roles vary considerably depending on the industry, business, goals and the day itself. Some common duties include:
• Meeting with the team to discuss projects and goals
• Identifying problems and potential solutions within projects and the larger organization
• Researching algorithms, methods and information pertaining to specific projects
• Mining different sources to collect data
• Cleaning data for accuracy and searching for patterns
• Merging data
• Testing models and rebuilding
• Meeting with stakeholders and others to discuss findings and explain data and recommendations
• Analyzing, visualizing and interpreting data
• Designing experiments
• Developing algorithms and predictive models
• Writing reports based on findings
• Using a variety of coding and data analysis tools
• Reading up on industry news and trends
Again, these daily responsibilities may not occur every day or across the board — there can be great variability based on different circumstances.
Data scientists should have a variety of hard and soft skills to get started in the field. They must, of course, be math- and statistics-oriented, with plenty of experience gathering and analyzing data. As mentioned above, most data scientists also have at least a master’s degree in data science or a related area, such as analytics or statistics. While it’s possible to land a job in data science with a bachelor’s degree, most employers prefer a master’s and some even require a PhD.
Hard or technical skills necessary for data scientists include:
• Software engineering and computer science
• Coding, programming and debugging
• Knowledge of mathematics and statistics
• Knowledge of business trends and practices
• Knowledge of machine learning
• Ability to make predictions
• Experience with software, data science toolkits, databases, algorithms and other platforms
• Business acumen
In addition to these technical skills, data scientists should also possess soft skills including:
• Verbal and written communication — particularly in terms of the ability to articulate complex finding and ideas
A data scientist should also be interested in uncovering solutions, identifying trends and answering questions. In fact, they should be the ones to ask questions that others have not thought to look into previously. And, of course, they should have a knack for collecting and interpreting data.
Data science is a highly lucrative profession. According to "Forbes", entry-level (1-3 years of experience) data scientists earn a median salary of $95,000, while more experienced professionals (9+ years) earn a median salary of $165,000. Managers’ salaries, meanwhile, range from $145,000 (with 1-3 reports) to $250,000 (10+ reports). This increases considerably based highest degree attained. For example, data scientists who have a PhD have a median salary of $102,000 in the entry-level category, compared with the median salary of $92,500 for the same level of experience among masters degree holders.
Data science can be a highly lucrative and reward path for those who are curious, passionate about and skilled in math and statistics and excited about uncovering solutions to problems within organizations. They play a vital role in shaping business strategies, goals and plans and are essential players in nearly every industry imaginable.
Of course, data science is not for everyone, but for those with the right skillset and interest in the profession, it can be a high-earning profession with great career satisfaction.
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