What is the Role of Data Scientists in the World of Big Data?
In a world that’s powered by data, the most beneficial 21st-century job skills to have been in the field of data science. Both data science and analytics have been cemented as important navigation tools that find applications across a range of industries. If computer science and problem-solving are among your top five skills, building a career in data science might be a great choice. But what is the job of data scientist and how do they power businesses? Let’s find out!
Job of Data Scientist
Data Scientist Skills
A good data scientist will have the right combination of technical and non-technical skills in their toolkit. We have compiled a list of important skills that enhance the job of data scientist.
Technical Skills:
- Programming languages like Structured Query Language (SQL), Python, Statistical Analysis System (SAS), etc
- Machine learning (ML) and deep learning
- Data visualization tools such as Tableau, PowerBI, etc
- Statistical analysis
- Data wrangling
Non-Technical Skills:
- Effective communication
- Proactive problem-solving
- Strong business acumen
- Solid critical and analytical thinking
- Good data intuition
ALSO READ: Top 11 Data Science Skills You Ought to Learn
Data Scientist Job Description
A data scientist is essentially hired to power an organization’s systems and solutions through data. They must have the right technical and statistical expertise to mine, interpret and extract data from various sources through ML tools. Moreover, they should enable smarter business processes by deriving useful data-driven insights that can help create a new vision for the organization’s future.
ALSO READ: Top 13 Data Scientist Interview Questions You Should Know
Data Scientist Roles and Responsibilities
The job of a data scientist goes beyond interpreting large data sets to derive actionable insights. These are the main roles and responsibilities of a data scientist:
- Extract and mine relevant data sources that match business needs
- Collect both structured and unstructured data sets to perform data analysis
- Develop ML algorithms and prediction systems
- Use ML tools to improve data quality
- Interpret data and ensure data uniformity to identify useful trends and patterns
- Collaborate with software developers and engineers to implement accurate analytical models
- Propose refined solutions and strategies to improve business intelligence
Data Science Careers
A career in data science is highly lucrative as the demand for professionals in this cutting-edge field is rising remarkably. However, the role of a data scientist is not the only job to pursue or aim for in this field. In fact, data science offers a diverse range of careers that are actually shaping the future. Here are some of the most popular roles in data science.
- Machine learning engineer
- Data analyst
- Applications architect
- Business intelligence (BI) developer
- Marketing analyst
- Database administrator
ALSO READ: Top Careers in Data Science: Average Salary, Required Skills and More
While the job role may sound promising, many people wonder what a workday for a data scientist looks like. Let’s give you a quick rundown!
What Does a Data Scientist do on a Daily Basis?
When the job of a data scientist involves managing large data sets and proposing business solutions, it is nearly impossible to have a ‘typical’ day at work. Each day would inevitably bring a new challenge. However, let’s try to decode what the daily responsibilities of a data scientist look like:
- Identifying data analytics problems and understanding pain points from the stakeholders’ perspective
- Gathering raw data to analyze defined problems
- Establishing an approach to solving problems using ML tools
- Optimizing models and sharing insights with stakeholders
The Data Scientist Career Path
Data science is still in its nascent stages, which is why there may not be clear precedence on what a conventional career trajectory in the field looks like. Most candidates have a bachelor’s degree in a technical field that covers foundational aspects of math and computer science. A majority then build on that with an advanced Master’s Degree in Data Science or a related field.
Generally, data science professionals kick-start their careers with entry-level positions like junior analysts or software developers and eventually move on to mid-level positions such as data architects or big data engineers. Once they have progressed to the role of a senior data scientist, most candidates then transition into management roles.
Data Scientist Job Titles
A data science professional can take on more than just the role of a data scientist. Since the scope of the field is so wide, each of these popular data scientist job titles is responsible for the role of managing data in some form:
- Data engineer: Designs, builds and manages big data infrastructure
- Data analyst: Interprets data sets to identify new trends and insights
- Data visualizer: Evaluates data analytics and creates visual aids to support business needs
- Data architect: Optimizes an organization’s logical and conceptual data systems
Data Scientist Salary and Job Growth
The salary range for a data scientist typically falls between $124,021 and $153,409, nearing an average of $139,202. As per the U.S. Bureau of Labor and Statistics, the employment rate for data scientists has been projected to grow by 36% between 2021 and 2031.
The driving force behind high data science salaries and increasing job prospects is that organizations are now truly understanding the power of big data. They want to leverage it to make smarter and more informed business decisions.
Data has truly become the currency of our age, which is the key reason why data scientists are in constant demand. There is a need for data scientists across varied industries, from government security and healthcare to finance and banking. To explore a career in data science, begin with exploring any of the data science and analytics courses offered by Emeritus and get started on your journey to becoming a data scientist today!
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