Data is the New Oil

Career Opportunities in Data Science in the UK, US, and Europe

Did you know that an average data scientist can earn up to £51,863/year? Almost every major organisation is looking for data science professionals. There is still a huge gap in the data science industry for talented individuals. This can provide great opportunities for students and professionals in the data science industry.

Every sector is looking for data science professionals. Seize the opportunities!

About the Webinar

This career-oriented webinar aims to provide a clear understanding of the present state of the Data Science industry and a path to define career opportunities. We will be exploring the top companies hiring data science professionals and their demands. “Career Opportunities in Data Science in the UK, US, and Europe” will begin on 24th July 2021, from 2:00 PM to 3:00 PM BST.

Key Details

  • Date: 31st July 2021
  • Time: 2:00 PM - 3:00 PM BST
  • Topic: Data Science

Why Should You Attend the LSET Webinar?

Today, data science is one of the hottest industries in the world. It is predicted that this industry will rise at a rate of 27.9 per cent by 2026. In this webinar, we are going to discuss the tremendous career growth opportunities in this industry. The attendants will get the chance to discuss their doubts and get proper guidance to engrave a career in data science.

Exclusive Highlight: LSET will be selecting 10 individuals from the webinar. These individuals will be provided with the opportunity to participate in our exclusive career preparation workshop on data science. These workshops will help you with the right way of labour and learning commitment to start your career in data science.

Register for the Webinar

Topics Discussed in the Webinar

  • Understand the spectrum of data professions
  • Understand the job market of data science professionals
  • Learn about the types of projects in data science
  • Learn about the exponential growth possibilities
  • Get help in the transition of career to data science
  • Engrave a path to your career in data science

Topics Discussed in the Webinar

  • Data science industry exposure
  • Career counselling to become Data Science professional
  • Clearing doubts and answering questions
  • Skills required to learn data science
  • Applications and impact of data science
  • The need for analytical tools knowledge
  • The required education qualifications
  • Strong business sense
  • CV preparation for data science jobs

Questions Discussed in the Webinar

  • Which programming languages to learn data science?
  • What is the expected salary and growth?
  • What is the best way to learn data science?
  • Can non-technical individuals learn data science?
  • Will experienced professionals have a faster learning experience?
  • Which data science role should you consider?
  • How can your existing skill-set can be useful in data science?
  • What are the challenges in transitioning a career in data science?

Who Should Attend this Webinar?

  • Enthusiast students who want to start there in data science
  • Individuals who are coming from a non-technical background
  • Professionals who are looking for a career change
  • Students who want to start learning data science

Why Should You Learn Data Science?

The Data Science industry is a very lucrative industry with high salary bands and diverse jobs. It consists of programming, problem-solving, and business domain. Data experts are responsible for playing a major role in business analysis and in the development of data products and software platforms.

  • Big companies like Google, Apple, Amazon, Microsoft, Facebook, and Netflix are some of the top employers of data science professionals
  • Learning additional programming languages can provide you with huge growth opportunities
  • The COVID-19 pandemic has created a huge demand for data science professionals
  • You can learn Data Science even if you are from a non-technical background

Career Options in Data Science

Data Scientist

This is a major profession in the data science industry. A data scientist is responsible for elaborating the importance of data and derive useful insights. They must have knowledge of different programming languages and statistics to solve complex problems.

Data Analyst

Data Analyst

Data analysts help organisations to get a clear picture of their business goals in the market. They have to provide huge datasets to achieve the needed goals. These professionals have to adapt according to the different companies and their requirements.

Data Engineer

Data Engineers are often regarded as the backbone of companies. They are responsible for building, designing, and managing large databases. These engineers also have to collaborate with other data experts to communicate results and insights.

Business Intelligence Analyst

Business intelligence analysts are responsible for analysing the gathered data to enhance an organisation’s efficiency and effectiveness. This role requires more technical skills than analytical skills. They form a bridge between IT and business.

Marketing Analyst

Marketing analysts have to help organisations in their marketing ventures. They have to constantly monitor customer satisfaction and product performance and improve existing products and services—their expertise help in driving more profits.

Statistician

Statisticians are the experts of statistical theories and data organisation. They are responsible for providing meaningful insights from huge data clusters. However, they are also needed to create and implement new methodologies for the engineers.

Top Data Science Employers

Amazon
Amazon
Microsoft
Microsoft
Oracle
Oracle
Facebook
Google
Google
APPLE
Apple
Accenture
Accenture

Skills You Need to Become Data Science Professional

These are the important skills that you need to have to make the best out of opportunities:

Basics of Data Science
Basics of Data Science
Programming Knowledge
Big Data
Big Data
Presentation Skills
Communication Skills
Statistics
Statistics
Data Manipulation and Analysis
Data Visualisation
Data Visualisation
Model Deployment
Model Deployment