Data science is one of the top-rising multidisciplinary approaches to technology today. Big data remains crucial as most organizations are seeking to improve their performance through data analysis. This has increased the demand for people who can gather, examine, and visually represent vast amounts of data. 

According to analysis, the data science market will grow at a compounding annual growth rate (CAGR) of 27.7%. That is to say, from $95.3 billion in 2021, it will grow to approximately $322.9 billion by 2026. It is expected that many sectors will contribute to this growth.

For instance, the proliferation of the Internet of Things (IoT), rising investments in research and development efforts related to machine learning (ML), artificial intelligence (AI), and also, cloud computing infrastructure and services.

Moreover, the ever-growing demand for data science across various industry verticals will contribute to this growth. The sectors include manufacturing, financial services, logistics, retail, and consumer goods. 

This growth will lead businesses to embrace AI/ML solutions faster. Therefore, this will increase the demand for more big data and data analytics experts. 

There are endless opportunities in this field. But today, let’s focus on some of the best data jobs to look out for in 2022.

Best Data Jobs 2022 has to Offer

1. Business Intelligence Developer

To become a business intelligence (BI) developer, you should be a skilled software engineer. You need to know how to use big data platforms to evaluate unprocessed data from an organization’s internal and external sources. 

Knowledge and experience in tools like SAS, SQL Server, Oracle, and R are vital. This will help you formulate effective business strategies based on their data analysis. Moreover, you’re responsible for producing valuable reports to help managers decide how to operate their operations. 

BI developers are increasingly becoming popular. Many businesses already use both on-premises and cloud-based business intelligence systems. Hence making BI developer a lucrative job in 2022 and beyond.  

Are you worried about where to get BI developers’ jobs? There are several data job openings on Only Data Jobs, including BI developer roles. The demand is there; you only need to up your skills and grab these opportunities. 

A degree in Computer Science or a related field and a master’s degree is an added advantage. Also, investing in certifications like Certified Information Systems Auditor (CISA), Certified Information Security Manager (CISM), and Project Management Professional Certification (PMP) will work to your advantage. 

2. Big Data Architect

Source: Pxhere

A data architect is also known as a chief data officer. This individual has a broad perspective on your company’s data and how to use it efficiently. 

As a data architect, you’re required to collect, categorize, store, manage, organize, and make organization data available. Besides, you’ll also need to concentrate on streamlining corporate procedures. Therefore, you need to have experience and knowledge on how to use technological tools like cloud computing and other digital platforms. 

If you have a bachelor’s degree in computer science or a related subject, you can work as a data architect. Also, having a certified data management certificate is an added advantage. 

Moreover, most employers will favor you if you have prior experience and expertise working with vast amounts of data. Additionally, proficiency in programming languages such as Java, Python, and C++ will help you stand out. 

Often you will need to suggest new technologies and systems and examine the best way to improve the existing systems. 

Also, you’ll need to be able to build new security or develop policy measures to safeguard private data from hackers and other cybercrimes as well as manage sensitive information. 

3. Data Scientist

Data scientist is another lucrative career in 2022. Your role as a data scientist will be to manage huge complicated datasets while providing results using machine learning and predictive analysis. 

Moreover, you need to use various tools and resources to aid commercial decision-making. These include statistical tools, machine learning, artificial intelligence, and data mining techniques. 

To get a job as a data scientist, you need to have a degree in mathematics, data science, or computer science. Moreover, you can leverage BootCamps since data scientists have a huge demand. 

Regardless of your area of specialization as a data scientist often, you will need to gather and clean datasets. Also, you will need to choose the right questions to ask, write code, evaluate the results and produce relevant reports with findings. 

4. Machine Learning Engineer

Machine learning engineering is increasingly becoming more popular as it helps reduce an organization’s operational costs.  Algorithms are crucial for machine learning engineers when solving problems. They use these algorithms to examine data, search for trends and differences and illustrate this data to reach a decision. 

Your job as a machine learning engineer is to counter-check the data for accuracy and quality before presenting it. Their primary role is to develop algorithms and programs that help machines to do tasks autonomously. 

Most machine learning engineers have bachelor’s, master’s, and doctoral degrees in computer science. So it’s a good idea to advance your career to qualify for this data science job. 

5. Statistician

You’ll need to gather, analyze, and evaluate data as a statistician to find patterns and connections that can guide business decisions. Statisticians also regularly advise on organizational strategy, communicate with stakeholders, and create the data collection process.

Since it combines statistical knowledge with other subject-specific expertise, this position is highly sought in both the public and private sectors.

6. Data Analyst

Source: Pix4free

You will create and maintain data systems and databases as a data analyst. Also, their other role is to examine and correct any coding mistakes. 

You need to have experience in using statistical tools for you to interpret data. Moreover, you need to give more focus on patterns and trends. This data is valuable when analyzing predictive and diagnostic analytics. 

To succeed as a data analyst, analytical and leadership skills are essential. There are a lot of opportunities for candidates with undergraduate or graduate degrees in computer modeling, analytics, physics, or mathematics. 

So if you’re a novice or a professional, here are some of the duties of a data analytic that you’ll be required to:

• Collect data and maintain the data systems
• Use statistical methods to evaluate data and provide reports
• Establish and use data collection systems
• Finding, analyzing, and interpreting patterns and trends in large, complicated data sets

Key Take Away

You shouldn’t worry if you have a skill set in data jobs. The future is still bright and wide with an astonishing array of opportunities. Big Data and its various uses are only at the inception stage. There are so many professions you can pick from. And your skills will be valuable in many sectors regardless of the business.

The post 6 Best Data Jobs of 2022 first appeared on NAZING written by Olivia Bradley

In the past 20 years, the amount of data generated and stored has grown exponentially. To meet the demand of the field, data science practitioners need to expand their mathematics, computer science, critical thinking, and problem-solving skills. The economy is like time. It doesn’t wait for anyone. And the time for the rustic professionals is running out with every new start-up and advancement in the business world.

Big Data is everywhere and there is almost an urgent need to collect and preserve whatever data is being generated, for the fear of missing out on something important. There is a huge amount of data floating around. Data Science has become crucial as it helps in advancing the business, decision makings and offering the biggest edge over the competitors.

Job role of a data scientist

The job role of a data scientist involves the following tasks on a day-to-day basis irrespective of the industry a person works in:

• Getting patterns and trends in datasets for unrevealing insights
• Developing algorithms and data models to foresee results
• Using the numerous Machine Learning (ML) methods to improve quality of data or product offerings
• Communicate recommendations to other teams and senior members
• Deploy data tools, such as the following Python, R, SAS, or SQL in data analysis
• Stay ahead in terms of innovations in the field of data science

Data Science Certification

According to a survey of 700 professionals, jointly conducted by Network World and SolarWinds, among the highest-paid IT professionals who had certifications, 58 percent said a certification led to a salary boost or bonus, 63 percent said it led them to get a promotion, and 30 percent to a new job.

Certifications – a term massive to express the plethora of implications and applications attached to it in today’s dynamic business conditions. If we were to jump into a time machine and go back a few decades, the word “Certification” would be redundant in many streams of business. A word that was traditionally associated with doctors, engineers, and other professionals. But today it has become the most essential booster for an individual’s career, irrespective of the line of business they are associated with.

Doing the best data scientist certifications are inexpensive definitive proof that an individual holds expertise and skills being current and up to the industry standards. You’re passing the industry’s measurement of your knowledge based on their skill assessments test of the designation you are being certified for.

A best data science certification is essential both personally and professionally. It is a career-long commitment that can help demonstrate to the peers and to the company that one is driven to become a successful data science professional. The prestigious Data Science credentials:

• Can help set an individual apart from those without it
• May help increase the professional confidence and satisfaction
• May maximize the earnings potential
• Can result in greater respect from the firm
• Makes an individual a better candidate for a new job opportunity

Retrain & Reskill

Retraining is the method of learning, refreshing, and developing data literacy skills in a workplace through continuous learning and training programs. It’s often needed on a regular basis to keep up with technological changes, regulations, and skills development.

Several industries from banking to manufacturing have become digitized. As a result, the World Economic Forum predicts that in the coming two years, tens of millions of jobs will disappear due to automation. At the same time, demand for jobs that require technical skills such as data science continues to rise while firms around the world are experiencing a skill shortage. To meet this skills shortage the employees need to keep up with latest technological changes.

Retraining employees in data science-related skills has thus become an essential need. Several organizations are following a high-level approach for up skilling their workforce for data science-related skills.

End notes

When it comes to careers in data science, it is important for helping employees understand the organizational goals and offer them proper retrain. The organizations should look for internally and start to realize the advantages of retraining their own employees in an effective way.

The post Time to Retrain and Reskill the Data Science Professionals first appeared on NAZING written by Olivia Bradley