Top 9 Data Science Career Opportunities

Getting top data science career opportunities is easily one of the most promising in the current times as well as the foreseeable future. Technological development runs with the development in the Data Science domain. This domain offers job opportunities with excellent salaries. The demand for data science specialists is rising, so it is an excellent opportunity for you to get into this field. 

Data science is a phenomenal career choice in India for growth, compensation, lifestyle, and the future. Data is expected to drive this and the next century as we exponentially advance in various industries. As there is a massive scarcity of specialists in this field. In this article, you’ll learn about the future of data science, the skills you need & the career paths you can opt for in this field. 

Bright Future of Data Science Domain

Among the top skills in demand today, artificial intelligence (AI) and machine learning (ML) are in high demand. Data scientists find linkages across massive datasets to offer trends and insights to gain a competitive advantage.  Insightful data facilitates decision-making across businesses today. Post-pandemic, most operations moved to digital platforms across businesses, stimulating e-commerce and volumes of data. Small and large businesses must process all this data, find efficient data collection strategies, and organize and analyze data to plan future contingencies. 

In 2021, Glassdoor showed nearly 40,000 data science jobs, including ML engineers, business analysts, data analysts, and financial analysts. The job growth & demand for data scientists are uphill; companies are desperately looking for skilled talent. Data scientists with expertise in major programming languages and advanced technical skills are more likely to get a job at higher-paying positions with lucrative projects. 

Primary Technical Skills Needed As a Data Scientist  

Learning new technologies and the latest extensive data analysis platforms enables data scientists and experts to stay relevant, equipping them with practical knowledge and hands-on training. 

• Important Platforms: Hadoop, Apache Spark
• Major Programming Languages: R Programming, SQL (Structured Query Language), Python, Java, C, and C++
• ML and AI: understanding neural networks, reinforcement learning, Natural Language Processing (NLP) technologies, recommendation engines
• Data Visualization: Matplotlib, Tableau 

 

Primary Non-technical Skills Needed As a Data Scientist 

Apart from the technical skills & knowledge, a data science professional must have certain soft skills as mentioned below: 

• Data scientists don’t usually work alone; they must be team players.
• Good analytical skills to analyze data, identify trends, and real-world industry challenges.
•  Good communication skills: Data science professionals must translate incomprehensible data into relevant, actionable strategies from C-suite to investors and sales teams. So and storytelling is a crucial skill.
• Collaborating on multiple projects and departments across the organization is a common feature.

Different Data Science Career Opportunities

There are many roles that a data science professional can fill in any industry. With the advancement of technology, new roles & responsibilities are developing daily. Here are the major career options available to a data science professional: 

1. Data Analyst 

Most data scientists start their careers as data analysts and engineers. Their work entails working directly with raw data collected through the systems. They also work with various teams, like marketing, sales, customer support, etc., to manage information. Data analysts don’t just run after the big business questions; they clean, study, and create reports using data visualization tools such as Excel, Tableau, etc., to help teams develop strategies. 

2. Data Engineer 

Data engineers are experts at accessing and analyzing vast amounts of data in real-time. They’re vital for technology-driven companies as they interpret unformatted and unverified data. Thus, their daily tasks include maintenance of high data volumes as well as making data pipelines to make data available for further analysis with the other teams. They also built the infrastructure using programming languages (Python), advanced SQL, and NoSQL. 

3. Data Scientist 

Unlike Data analysts, Data Scientists go beyond analyzing data to address business problems. The C-Suite relies on data scientists to generate trends and patterns across datasets and offer insights and strategies that can work the bottom line. Their insights need to have a direct impact on strategic & crucial business decisions. Apart from this, they should be excellent communicators, business strategists, and even better analysts and statisticians.

4. Data Architects and Administrators

Data architects & data engineers work together to visualize the data management framework for the entire organization. They primarily work on understanding the organization’s strategy and data that needs to be analyzed after collecting. They then create new database systems and increase the performance of existing systems. Data architects design data collection and management processes, and data engineers develop the infrastructure. 

5. Machine Learning (ML) Engineer 

An ML Engineer is a unique combination of software engineering and data science that works with big data daily. Both roles work together in a sizeable consumer-facing setup but may have independent responsibilities. Data scientists must be ML experts with advanced software programming skills. Machine Learning Engineers develop software, ML models, and AI systems to drive various processes for the organization. Advancing to an ML engineer takes years of experience and expertise, so typically they are recruited in senior roles. 

6. Business IT Analyst 

A business IT analyst is essentially a strategist at heart and an analyst by the mind. They evaluate a company’s processes and analyze industry & market trends. Business analysts use massive data and scout opportunities to improve business revenue and growth. Common job titles are business intelligence developers and business consultants. Processing this data requires a Business intelligence developer to have advanced skills in BI analytic tools and programming skills. 

7. Clinical Data Managers

Clinical data managers combine healthcare training with mathematics, programming, computer science, and statistics. Like the other fields, data collection to data governance and integrity across clinical trials and research, clinical data managers assimilate, analyze and predict medical industry trends.

8. Marketing Analyst

Identifying shifting consumer behaviors, examining new buying trends, and analyzing a business’s digital universe are all the excellence of a market analyst. As most businesses sell digitally, marketing analysts access large amounts of data across various platforms and devices to create robust go-to-market strategies and evaluate marketing campaigns.

9. Statisticians and Mathematicians

Prominently working with the government or R&D organizations, statisticians recognize trends that advise decision-making and policies in various organizations. As the name suggests, mathematicians and statisticians interpret vast volumes of numerical data, design research surveys, develop mathematical models to collect data, and report findings.

The data science domain offers thriving career opportunities and many job roles for those interested. Therefore, persons with a bachelor’s or master’s degree in Computer science (CSE) can easily consider building their careers in data science by reskilling & upskilling through online data science course . 

Summing Up!

The scope of data science anywhere in the world is bright. The best part about this domain is that you can choose to learn data science & related skills from your home and get a high-paying job. Skill sets are often deciding whether you bag a high-paid job or not. We hope this article provided you with insightful information about job opportunities for data scientists.

Further, Brainalyst’s all-encompassing Data Science program can help you ace advanced data science concepts through practical hands-on experience and industry-relevant skills.