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The role of a data scientist has garnered an immense reputation in the industry. With generous paychecks and respect, the role seems highly technical. It is a sophisticated role that requires a gamut of skills. However, these skills can be learned in a few spans of months and get started in a job.
Data Scientist’s role in the industry
A data scientist is a multi-disciplinary role, which requires good programming skills, knowledge of statistics, and machine learning. These are skills are used to help businesses make decisions. A data scientist takes data from various silos of a business, which could be various applications (CRMs, automation tools) or external sources (public datasets) and analyze them to find actionable insights.
Businesses act upon these insights that ultimately lead the business to the desired goal. The role of a data scientist can be summarized as – collect, analyze, and build.
- Collect – collect relevant data pertaining to a problem. For instance, a healthcare data scientist working toward predicting the risk of cancer in patients would collect data on cancer patients.
- Analyze – Analysis
of collected data to ascertain hypothesis. A hypothesis is an assumption based
on previous research or experience. The analysis helps to reject or approve a
hypothesis. Sometimes leads to new discoveries. For instance, a data scientist
may find a correlation between two factors that we thought were completely
unrelated.
- Modeling – Build a predictive model based on research that yields results on its own. Don’t expect data scientists to keep working on the same problem again and again. Once a solution is derived, it is converted into a machine learning-based predictive model that yields results on its own and gets better with time.
In a nutshell, data scientists are problem solvers in the industry. And as we know from the nature of jobs, problem solvers are highly rewarded. According to a Robert Half Technology Salary Guide, the average salary of data scientists is $125, 250.
Data-driven strategies are replacing traditional decision making processes everywhere. Thus, demand for data scientists is across the industry – from retail and manufacturing to financial services and healthcare. Data scientists are now a revered professional.
To get a junior data scientist role, a bachelor’s degree in statistics, computer science, engineering, or any other technical field is enough. For higher positions, pursuing a master’s degree, Ph.D., or a global data science certificate is an ideal option.
Let’s take a look at the skills you need to become a data scientist.
Skills for a data scientist job
A data scientist requires the following skills —
1. Statistics – This is the foundation of data science. Probability functions, distributions, measures of variance, measures of dispersion, measures of central tendency are some important and frequently used concepts that help in understanding complex statistical methods. Additionally, good mathematical skills complement statistics.
2. Programming – Statistical techniques that were earlier implemented manually are now done programmatically. With pre-defined functions and packages, performing statistical techniques programmatically is easier. R, Python, and SAS are used worldwide for this purpose.
3. Machine learning – Predictive modeling is enabled with machine learning algorithms. Time-series forecasting, regression, random forest, classification, and more are a few algorithms that one needs to know.
4. Data visualization – Data scientists also have the responsibility to communicate their findings to stakeholders in a clear way. Tools like Tableau, Privacera, and in-built Python packages like Matlplotlib, help data scientists do that with ease. These tools help data scientists to visualize data and results in the form of easily understandable charts and graphs.
5. Communication skills – Data scientists join a high rank and report to management leaders, which requires and for communication. Good communication skills make expressing ideas, problems, and challenges easier, which are a core part of a data scientists’ job.
Initially, in a junior role, all these skills aren’t required. But as you grow, each of the above skills becomes increasingly important. A few data scientists choose to continually learn and improve their skills by taking a data science certificate, pursuing higher education, or working projects outside work.
Conclusion
All in all, data scientists are problem solvers who use data at their disposal to help companies solve problems. If you want to become a big data scientist focus on learning skills and solving problems using data.
