Skills Required for a Data Scientist
In every business, we encounter critical problems which hinder the business potential. Every organization must work on the resolution of the critical business problem at earliest. In fact, they should be able to predict the problem before occurring and resolve it to avoid losses. Is this even possible for management to predict events occurring in the future? The answer is yes. Let us see how.
In earlier times due to lack of data and technology, it was difficult to predict and resolve problems quickly, As it was still done on the basis of vision and vast management experience, it was not based on data but more on individual skills of management. However, with the advent of technologies such as artificial intelligence, machine learning, data science, and big data, it is possible to collect, store and analyze huge historical data to predict future events and propose innovative solutions. In addition, proposed resolutions are more reliable and accurate as all are based on the data collected over long periods of time.
Since data is key to problem-solving, organizations are creating dedicated teams inhouse for data wrangling. Several new roles as well as credentials, like a data science certification, have come into existence in the last decade to help management with a critical business problem resolution. Significant efforts and money is invested across organizations to develop in-house teams of experts to leverage tools and technologies beneficial to the business. In addition, efforts are made to ensure effective utilization of the huge potential of historical data to improve current products or services and enhance customer satisfaction.
Data scientists along with other roles dedicated to the handling of large data sets are becoming very popular. All of these roles involve a good understanding of new tools or technologies and work closely to solve business problems. In the current article, we will concentrate on understanding more about data science roles, responsibilities, and skill sets.
What is a Data Scientist?
In a nutshell, a data scientist works closely with data engineers, together they collect data relevant to business problems, analyze and summarise it to find possible solutions. As the name suggests it is a scientific and research-based role, as every business problem has a unique set of data and solution which has to be explored by a data scientist.
Data Scientist Roles and responsibilities
Some of the key responsibilities handled by data scientists are listed below
- Data exploration and research to gather data against the business problem.
- In the case of multiple business problems, prioritizing the most critical along with the extended team and customer.
- Work with data engineers to collect, filter, and process input data in usable tables.
- defining critical inputs for mathematical modeling.
- Developing algorithms for identifying data patterns and trends.
- Developing modeling for future event predictions.
- Validation of models and implementing on larger data sets.
- Improvement in existing models based on further data collections.
- Summarising finding reports and regular updates to teams.
Skills of a Data Scientist
Some of the key skills preferred for data scientist role are listed below
- The advanced programming language skill is a must for any data scientist. In current trends, python is used extensively by data scientists to develop algorithms. Python is preferred due to its extensive library and data handling capabilities. Numpy, Scipy, and Matplotlib are some of the key modules used frequently by data scientists and machine learning experts.
- Data scientists may need to work on historical data from various sources. It may be structured or unstructured data. A data scientist must have a good understanding of various data sources, formats, and data integration.
- Since data size and volume are immense, data scientists should have good knowledge of Big Data Frameworks and Tools.
- Data scientists sometimes have to develop mathematical models which mostly are based on basic and advanced statistical tools such as curve fittings, regression analysis, numerical integration. A data scientist should have a strong knowledge of statistics and mathematical concepts.
- Data scientists along with data engineers might need to work on querying data, therefore it is recommended to have experience in data querying.
- Data Visualisation tools are important for summarizing data and preparing dynamic reporting. Hands-on experience with tools like tableau, Powerbi is preferred.
- Problem-solving skills are most important for data scientists as data scientists need to gather data and filter out the data from historical data relevant to the problem faced. Therefore he should be able to understand the problem statement clearly and understand it thoroughly.
- Communication skills are important as data scientists need to communicate with team members and customers for the understanding of the problem and present the final solution effectively.
In summary, tools used mainly involve Advanced Python programming, SQL, Statistics, Apache Spark, Machine Learning, Data Mining, Tableau. However, this list is not exhaustive and you may need to learn based on the exact requirements.
Organizations seeking a data scientist
Software Companies like Microsoft, Google, Twitter, IBM, Amazon, Accenture are preferably using data science along with new domains such as automotive and aerospace companies like BMW, Volkswagen, GM, Tesla, Boeing, Airbus. In fact, the data science role is becoming popular across the industry to help them with research projects.
Salary and Demand
Due to research-based roles, data scientists are one of the important roles in current conditions. Many companies prefer to hire good data scientists to help them with problem-solving, research, and development. Data scientists can help companies to improve their products or services through extensive data analysis. The demand for data science roles is growing since the past many years and will do so in the future as well.
Skilled data scientists are paid decently in every field. According to glassdoor , the average annual salary of a Data Scientist is $1,13,309 (In the United States).
Conclusion
With the world moving towards innovation and new technologies, research-based roles are in high demand. Data science is one such role where both good software and engineering skills are used to help companies develop high-quality products or solve issues in existing products proactively.
If your interest lies in research-based work along with excellent software engineering and mathematical skills, this is the field you should make your career in. To start your journey you can opt for a good training program preferably an online course. Build the skills required to be a successful data scientist with comprehensive training and get yourself certified before joining a prestigious organization and contribute to their great product.
Hope this article has given you some insight into the topic at hand.
Thank you for writing such a useful and interesting article.