Why Industries Lean On Data Science Courses to Tap Best Talent?

Photo of author

By admin

The global data science industry has been in a lot of churns in the recent years. According to the latest statistics and trends, the data science industry is expected to generate 50x more jobs in the next five years, providing salaries to the future data scientists in new and upcoming business domains. With growing salaries and industry specific opportunities around the world, countries like India have a real chance to stay on top of the game. The data science course in Gurgaon is one of the most searched keywords in the current league of top professional movements that sweep the job market. So, how is the current job market looking for the professionals and data science analysts looking to gain good leverage from the best of data science courses in Gurgaon?

In this article, we will highlight the growth trends in the industry where data science applications are widely used.

Data Science Accelerates Digital Skills

In every digital skill that you acquire, data should be a key factor.

Marketing and Sales jobs have been in a huge demand. Even the biggest of marketing and sales organizations are hiring from top notch AI and data science schools to close the gaps in their business analytics workflows. By using data science as a backbone of their digital transformation journeys within the organization, top hiring managers are able to fully justify their faith in the top courses in machine learning and business data analytics. In essence, top data science jobs in the country are majorly tapping the best talents who are able to use their hard skills in business intelligence and leverage available resources and technologies such as marketing automation, CRM, Email marketing, social media monitoring, and customer experience management to give a sense of accountability and high value of return from their marketing and sales. Companies that heavily use digital tools require people with a strong data science background. The future of digital is, therefore, data science.

Hiring based on data science 

Hiring managers who look out for data science talents themselves require some sort of background in working with people’s data, also called as human resources data – these could be sourced from different places, such as job boards, online job workshops, conferences, LinkedIn-type websites, and applications and contact us forms that are put up on the company’s hiring webpage. In most cases, this could be considered as a readily available data. However, advanced data analysts who work with hiring managers and business leaders in the recruitment industry rely on historical people’s data (candidate’s data / employee data/ alumni data) to identify the key factors that govern the trends in the job marketplaces. For example, people with an IT background are more likely to look out for roles that seek experience in coding and cloud management services. Keywords could be Python programming, data visualization, risk assessment, cloud security, etc — all of which could be analyzed for performance like any search engine management and keyword discovery tool for marketing—but only in this case, it would be useful for the recruiters. Data Science recruiters essentially ensure that they are able to use the best of data analytics and predictive intelligence based on Python and Machine learning programming to find and onboard the top of the line talent from diverse backgrounds who pose unique skill sets and a wide range of experience in working with different projects.

Financial Health Management

Being profitable and being an investor’s magnet are two different things. Data shows that a majority of the startups are not able to become profitable, however, they are able to gain the confidence of shareholders and investors very quickly. Only a handful of companies are able to become profitable as well as have a strong shareholder’s trust. These companies use big data and business intelligence for their financial and accounting management based on their SaaS and cloud investments. These companies are also super efficient when it comes to managing their financial data — a huge challenge in the current era where data hackers are always on the lookout for vulnerabilities and steal customer data worth millions of dollars. But thanks to advanced machine learning concepts, finance managers are able to curtail the difficulties through risk analytics, real time analytics, financial data management, and much more. With a solid background in Microsoft Excel, Microsoft BI, and Tableau, you can easily scale the biggest challenges in business operations. That’s why businesses are leaning on data science to stay competitive longer.