One of the most desirable jobs of the 21st century, data science opportunities secured the numero uno spot in Glassdoor’s ‘Best 50 jobs’ and ‘17 best jobs that pay over $100,000’ listings. More development and research in data science is observed in recent years due to the increasing shift and dependency towards automation and data-backed analytics and solutions to problems in business or operations. Ever since it was conceptualized, it has been providing services and upgrades to various industries and sectors. Data science, being used in IT or software development firms and other industries, requires other industries, requires data scientists to help organizations with automation or analytics and insights.
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What Skills Are Needed to Be a Data Scientist?
There are a few fundamental skills that are required for a career in data science. Also, some skills are job role-specific and only required for certain data science processes. But, here are some foundational abilities that a data scientist must possess. Have a look at the following data scientist job requirements:
- A data scientist must be comfortable with identifying patterns within data. They must be capable of detecting anomalies and proficient in statistical analysis.
- They must be skilled in machine learning (ML) and capable of using the related models or algorithms to assist machines in learning from data.
- Data scientists must possess networking and computing skills that enable them to use the principle elements of software engineering, numerical analysis, and database systems.
- They must be proficient in implementing algorithms and statistical models that promote artificial intelligence (AI) and other IT processes.
- Data scientists should be fluent in programming languages like Python, which allows them to write codes, model, and frame a program that can further analyze massive datasets or provide solutions for various problems. They can also work with Standard Query Language, R, or Java, which are equally effective though not as popular as Python.
- They must be good at storytelling and creating graphical representations of data to provide insights to stakeholders.
- Data scientists must be good at analytical or critical thinking to help provide data-backed insights and solutions to business problems.
Data Scientist Job Description
A data scientist job description consists of all the data scientist job requirements that one must fulfill when employed as a data scientist. A Data Scientist’s job description can vary depending on the companies or projects one is involved with, but basic requirements fundamentally remain the same for all roles. There are many roles and skills required for a data scientist, and some of these are:
- Identification of various sources of data and automation of data extraction or collection
- Undertaking the prior processing of data and sorting structured and unstructured data
- Analyzing massive amounts of data for the discovery of patterns and trends
- Building predictive and forecasting models using algorithms and the implementation of ML
- Combining data models using the process known as ensembling
- Storytelling to non-technical staff or stakeholders using immersive data visualization techniques
- Providing data-backed strategies and solutions to tackle business problems
- Data mining and noise removal
- Administering databases for clients or organizations and handling valuable data
- The role of a Data Scientist is to ensure the smooth processing and sorting of data in sensitive environments
You may also like to read: Is Data Scientist an IT Job | Learn About Various Roles & Skills
Are Data Scientists in Demand?
Data scientists are highly in demand, and this will not change anytime soon with the dire need for automation to make our daily lives even faster and easier. MNCs, government agencies, and startups need to hire data scientists to fulfill their data needs, such as understanding, processing, and extracting value from generated data. Organizations also require the assistance of data scientists to visualize data, gather insights and communicate the findings. Besides, LinkedIn published a report which ranked data science opportunities as one of the top emerging jobs in 2020.
According to the prediction by the U.S. Bureau of Labour Statistics, the demand for data scientists or computing and IT scientists has been projected to grow by a massive 15 percent between 2019 and 2029. And, with not many people yet lining up to be recruited by the top employers, there are ample opportunities and prospects for all the budding data scientists out there.
It is the same case across the world. Glassdoor reported 4184 current job openings in the U.S. with a median base salary of $110,000. Notably, there is ample money to be made as data science salaries in cities like Chicago, New York, and Seattle.
An average data scientist salary is quite desirable with many perks from the employing organizations. With thousands of jobs for Data Scientists worldwide inviting them to work in local corporations and MNCs, many career prospects with a high return on investment in learning data science and opting to be a Data Scientist.
Read more about how Data Science salaries fare in India as per our latest industry reports.
Why Do Companies Hire Data Scientists?
Companies hire data scientists due to the critical and analytical thinking skills they offer during figuring out solutions for many business problems. Data scientists are required to analyze the massive amounts of structured and unstructured data collected by companies to discover patterns inside them, use these patterns to figure out trends and provide valuable insights. Data scientists are required for handling data, interpreting it and effectively utilizing insights to power data-centric processes or help make data-backed decisions. Skilled data scientists are also mandatory to enable ML methodologies in computers and machines and for researching on improved AI or automation.
Here are a few reasons why data scientists are essential for companies:
- Finding analytical solutions for abstract and random business problems
- Applying analytics and conducting objective analysis of information to come to resolutions
- Going deep and discovering trends within the data to make improvements and predictions
- Communicating with stakeholders to understand business problems that need to be solved and divulging the results of data analytics or the insights to non-technical members of the organization through presentations and immersive storytelling
Which Companies Hire Data Scientists?
Tableau: It is one of the biggest recruiters of data scientists globally. Tableau is one of the most important data-centric companies out there, and its motto is to help the world see and understand data. It is involved with harnessing data skills, analytics, and ubiquity to better humans and society. Tableau requires hundreds and thousands of data scientists to assist it in its mission to improve the adaptability and efficiency of data. This company’s data scientist job description requires only the best and the most skilled data scientists in the industry. Also, Tableau is truly known as an employee-centric company that does everything in its power to keep employees happy. Joining this company opens up huge career prospects and new career paths which one can follow to reach greater heights.
IBM: An IT giant, it is also one of the earliest investors in the concept of AI, data science, and ML. IBM is responsible for many AI and data analytics innovations to the point where it is synonymous with computing and networking now. Huge deals with government and international bodies create even more jobs for data scientists in IBM, where there is a huge requirement for skilled analysts and individuals acquainted with the subject. The IT company recruits thousands of data scientists every year worldwide but is specifically heavily responsible for providing many data scientist jobs in India.
NVIDIA: It specializes in hardware manufacturing but is increasingly becoming more and more involved in the fields of AI and virtual reality (VR). NVIDIA uses its advanced hardware and experience in computing to create amazing augmented reality experiences with crucial support from data science. It is also known for creating brilliant AI systems which can be implemented in video games, deep learning applications, system development, and improved hardware designing. NVIDIA is a huge corporation and is one of the best companies a data scientist can join.
Ernst & Young: It is a global company that has started the heavy recruitment of skilled data professionals leading to many Data Scientist jobs in India. Ernst & Young is looking for talented data scientists with backgrounds in AI, business analytics, data analysis, cybersecurity, ML, and other fields which involve working with data and within sensitive data environments.
Accenture: It is also an immensely popular IT company that is on the lookout for many data scientists. Having many clients who require analytical and data-related services, Accenture is in dire need of data scientists. Also, Accenture handles many data-centric IT and BPO processes, requiring a huge amount of workforce skilled in data science and analytics.
These are some of the global heavyweights of the Data Science industry. You may also like to read more about Top Analytics & Data Science Companies in India
Becoming a data scientist is one of the most reputable and desirable career paths in the 21st century. It offers interesting job roles in which one can truly contribute to the betterment of society and technology that will take us further into the modern age and ease our daily lives. Data science is truly an interesting field with much to offer regarding career prospects and exposure to new things. Data scientists are highly valued by organizations and the modern world, with businesses becoming more data-centric and humans becoming more and more dependent on technology and automation. If you have opinions on this subject or any queries, drop us a comment below, and we will get back to you!
FAQs – Frequently Asked Questionsns
Q1. How can I become a Data Scientist?
There are a few criteria that one must fulfil before being recruited or employed to perform the role of data scientist. Have a look at the basic qualifying factors and skills required for a data scientist:
- Experience of working on data science projects or in the data analytics domain
- Skilled in data mining
- Good understanding of ML and AI
- Knowledge of programming languages, such as Python and R with the know-how of Scala, C++ or Java
- Skilled in the use of business intelligence tools, such as Tableau and frameworks like Hadoop
- Strong analytical skills with a good hold over mathematical concepts like statistics and algebra
- Problem-solving abilities and will to provide solutions to given problems
- Good communication and visualization skills along with the ability to prepare advanced graphical presentations and storytelling
- A degree in IT/computer science/data science or an accredited data science certification from any well-reputed institute
For more details, please also read: How to Become A Data Scientist- Step By Step Guide
Q2. How do I start learning Data Science?
You can get started on your journey as a budding data scientist by beginning from the foundation first. Good books on data science and well-orchestrated modules or courses can also help to get acquainted with this specialized field. Data science has a few technical requirements as well, which can be taken care of by learning a programming language like Python and brushing up statistical and mathematical concepts or algorithms. All of this can definitely give you a good start in your career as a data scientist and a major edge before getting professionally involved with data science.
For more details, please also read: How to Learn Data Science from Scratch?
Q3. Which language is better for Data Science?
Python is one of the best programming languages which is especially suitable for data science. It is mainly used for advanced analytics and data analysis as it enables easier access to data and provides the capability of using data effectively. Python is very versatile and promotes a huge chunk of functionalities with support for open-source libraries.
Python, being a cross-functional interpreted language helps in the rapid development of models and scripting of programs. It is dynamic and great for visually representing applications as well. It is highly preferred due to its compatibility with most data environments and high usage in mainstream IT and ongoing data science projects. Python is also highly loved due to it being easy to learn and the availability of ample amounts of learning material.
For more details, please also read: Why Python for Data Science is Industry’s Top Choice?