What are Some Important Data Science Careers?

Introduction

In the technology industry, data science is one of the most sought-after career paths. Data scientists combine code with statistics and perform data analysis, mining, and programming. A Return on Investment (ROI) or social impact measurement can be derived from these insights.

We use data science to track political campaigns, restock grocery stores, and keep medical records. It is an interdisciplinary field that plays an integral role in society’s basic functions. Being a part of this growing field can be an interesting and fulfilling career choice.

The field of data science offers various career options. The following guide explains what data science is, what skills are needed, how to get into the field, and how to get hired.

What is Data Science?

As a new specialty, data science emerged from statistics and data mining in 2002, when the Data Science Journal was established. As well as falling under the categories of computer science, business, and statistics, it sits at the intersection of software development, machine learning, and research. In government agencies, companies, and other organizations, data professionals create algorithms to interpret data patterns.

There is a need to make sense of the growing complexity of Information Technology, which is why data science exists.

What are the Required Data Science Skills?

To be a successful data scientist, one should possess excellent analytical and programming skills. They also need to possess various skills depending on the requirements of the specific organization.

To succeed in this career, it is necessary to possess two types of skills, technical and non-technical skills.

Technical Skills

A successful data scientist must have a strong understanding of computer programming, mathematics, and statistics to do their job well.

Aside from these skills, there are other skills that are needed:

• Analytical tools knowledge such as SAS, R, Spark, and HADOOP
• Data management capabilities across different channels for unstructured data
• Expertise in coding languages and computer programming

Non-Technical Skills

There are several types of non-technical skills possessed by an individual. These include:

• Communication skills
• Strong business sense
• Data intuition

Excellent Data Science Careers

To grow their businesses, data science strategies are being adopted by many companies. Data scientists are in demand, both in the technology sector and other major sectors like logistics and FMCG. The 5 biggest companies, Amazon, Google, Facebook, Microsoft, and Apple, employ approximately one-half of all data scientists in the world. It is commendable to mention that these companies are among the world’s largest.

The career possibilities in the field of data science are, however incredibly diverse. If you decide to pursue a career in data science, you will have access to a variety of career paths and job titles.

The following are some of the most lucrative careers in data science: You can enroll in a complete data science course to begin a lucrative career in data science.

Data Scientist

To measure the impact of an organization on data, data scientists analyze various data patterns. One of the key roles of a Data Scientist is to be able to explain the importance of data in a simple, easy-to-understand manner to anyone else. For solving problems, they must possess knowledge of various programming languages and statistical knowledge.

Data Analyst

As a Data Analyst, one of the main responsibilities is to analyze data to determine the market trends and provide a clear picture of the company’s position in the market. As soon as the company has set its desired goal, the Data Analyst provides datasets to contribute to the accomplishment of the goal.

To understand consumer behavior and their reactions to different marketing strategies, the Data Analyst role may change depending on what the company needs from them at any given time. For example, the department of marketing may require the services of a Data Analyst frequently.

Data Architect

To become a data architect, you need to first master data science. A data architect is a person who develops, designs, and maintains business’ data management systems. In addition to fulfilling the company’s database requirements, they are responsible for building those databases in accordance with the company’s internal and external policies and regulations.

Data Engineer

The Data Engineer is considered the company’s backbone. In addition to building data pipelines, ensuring data flow is correct, and making sure the data reaches the appropriate departments, they are also responsible for designing, managing, and building large databases.

Essentially, a Data Engineer is responsible for working with other data experts and sharing results with him and his colleagues. A Data Engineer is responsible for sharing his insights with the organizational leadership through data visualization, thereby contributing to the company’s success.

Machine Learning Engineer

As one of the most popular roles and careers in data science, machine learning engineers are primarily responsible for automating the analysis process of data. In addition to designing and implementing machine learning systems, they optimize and research machine learning algorithms and perform machine learning tests to ensure that the system works properly and is performing as expected. Recently, one of the most important careers within data science has emerged.

Business Intelligence Analyst

Business intelligence analysts are responsible for analyzing the collected data so that the company can maximize its efficiency and profits. They play a more technical role than analytical professionals, which means that they need a thorough understanding of popular machines to be effective. In addition, they must serve as a bridge between business and IT, improving both areas.

Marketing Analyst

Marketing analysts play an important role in assisting companies in their marketing divisions by analyzing and suggesting products to make in large quantities and products to discontinue in the future.

Database Administrator

As a database administrator, you are responsible for ensuring that the organization’s database system functions properly and safely. Additionally, you are responsible for creating backup and recovery solutions, and managing and storing your data securely.

How Much Does a Data Science Career Pay?

There is a high demand for Data Science, which is why it pays well.

Depending on your location, additional skills, and experience, you can expect to earn around Rs. 4.96 lakhs per year as the base salary in India, which may include an additional Rs. 50 thousand in bonuses. This salary can be as high as Rs. 9.98 lakhs per annum, based on your experience, extra skills, location, and employer.

In general, the income you are likely to earn increases with the amount of experience you have. If you have experience as a data analyst, you will earn approximately 157% more than someone with no experience. When it comes to those with mid-level experience, they will also earn 45.5 % more than those who have less experience.

If you possess any additional skills, you may be able to earn a higher salary. If you are proficient in data analysis, you will be able to earn around 4.5 lakhs each year. If you have expertise in SQL, you will be able to earn about 5 lakhs a year.

How Can I Start a Career in Data Science?

A certificate or course will give you the skills you need, but you’ll need some work experience to bring those skills to life.

Entry-level Job

You will want to apply for jobs in the field of data science that specifically cater to those starting out in this field to ensure that you receive the support you need as you prove yourself, develop your skills, and advance in your career. If you are successful in landing your first job or internship, you can expand your career opportunities.

Data science jobs are in high demand, so don’t get discouraged, because you’ll be rewarded for your hard work.

Interviews

You should practice expressing your process to a non-technical friend once you have secured an interview. Assume that your interviewer has no knowledge of your project, so you can discuss the tools you chose and the reasoning behind the algorithm you coded. The language and systems you will use on the job need to be proven to you.

Conclusion

There has been an unprecedented growth in the number of people working in data science fields, making it one of the fastest growing and most popular career options out there. Data science is considered one of the top jobs in the world.

If you’re willing to pursue a career in the field of data science, then you can enroll in Knowledgehut’s complete data science course and move further to building a career in data science.

FAQs

1. What is the career outlook for data science?

The field of data science offers many opportunities in the future for advancement and is a desirable career path.

2. What are the best degrees for data scientists?

To become a Data Scientist, it is often necessary to obtain a bachelor’s degree in one of the relevant fields, such as statistics, data science, or computer science.

3. What is better for data science, Python or C?

Python is one of the most commonly used languages for machine learning and data analysis. As a result of its simplicity and the support system it has for AI and machine learning frameworks, Python is an excellent choice for machine learning applications. Although C can be used for machine learning purposes, it is a less desirable choice.

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