How Your Telecommunications Experience Will Help You Launch a Career in Data Science

telecommunications and data science

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The telecommunications industry has been impacted by big data – big time. So it’s only natural that the skill set is a good foundation for a career in data science. Learning how to use it offers many employment prospects. With a background in telecoms, your programming, cloud and other IT skills already place you ahead of the curve. 

But first, telecoms professionals need to upskill in the tools and techniques of data analytics, data visualisation and machine learning. Then, take a deep dive into the growing, lucrative job market of data science. 

Why the telecommunications industry needs professionals with data science skills

With the rise of smartphones and connected mobile devices, the industry processes massive amounts of data. The infrastructure is evolving to accommodate the increased flow of data generated by millions of mobile devices. Telecoms companies have used big data to:

  • drive innovation and improve operational efficiencies by using predictive analytics for a better overall customer experience
  • enlarge scale with 5G technology to offer more services
  • increase machine learning tools to reduce infrastructure costs and customer turnover rate
  • detect fraudulent activity.

Research conducted by market research and consulting company Grand View Research Inc estimates the global telecoms analytics market will grow at a compound annual growth rate (CAGR) of 14.5% over the next six years. This will mainly be driven by big data. As a result, the demand for telecommunication data scientists will rise. 

Training in data science allows telecommunication professionals to leverage existing data and interpret the results to improve the customer experience. 

Ready to progress in your career? In an industry thriving on personalisation, enhanced customer experience, network optimisation and social media analytics, qualifications and experience in data science will make you extremely employable and valuable in today’s job market. 

Telecommunication companies are finding new ways to implement big data solutions

The industry has realised the significance of artificial intelligence (AI) and data analytics with a sizable investment. Both have an impact on all telecom functions from research, new product design and development, to sales and customer service. A report by research and consulting company MarketsandMarkets Inc estimates investments in AI will reach close to US$2.5bn by the end of 2022, with the Asia Pacific region accounting for the largest chunk.

Here is a list of top telecommunication companies in Australia and Singapore. These companies are implementing AI into their business processes to capitalise on data overload. 

In Australia

  • nbn

nbn has been using data science tools and techniques extensively to solve company-wide problems in telecoms by implementing virtualisation, network-IT convergence, machine learning and analytics. nbn is using innovative solutions to overcome challenges in an open, collaborative and experimental culture. This includes increasing responsiveness, effective decision-making and high automation. 

  • Optus

Optus, one of Australia’s largest telecoms companies, is pushing itself towards becoming a world-class, mobile-led digital service provider. Optus is aiming to power the next generation of products with data science and analytics. Recently, Optus built a data centre of excellence team to explore the scope of big data. Optus is actively seeking professionals in data science, big data engineering, advanced data visualisation, data governance and machine learning to join its team in Sydney. Learn more.

  • Vodafone

Telecommunication giant Vodafone is strengthening its operations, reporting and network visibility. Vodafone entered a multi-year agreement with Splunk, a software data collection and analytics company, to enhance Vodafone’s capability to identify and overcome customer-facing and back-end issues. Customer experience has been the top priority in telecoms. Vodafone intends to keep up with the growing competition by using predictive and proactive analytics to meet customer needs and help ensure higher customer satisfaction. 

In Singapore

  • Singtel

Singtel in Singapore has implemented a company-wide digital transformation to adopt data and digitalisation across all its departments. It created DataSpark as a subsidiary to provide data analytics and intelligence to a wide range of organisations. 

  • StarHub

StarHub has placed its main focus on growing customer relationships and reducing customer churn rates by using Salesforce to collect valuable customer insights. StarHub uses data analytics and data science technology to notify sales reps to contact customer’s before their contract expires.

  • Circle.Life

To improve customer experience, Circle.Life created a “virtual world” for its customers on its AI-driven digital platform. Circle.Life is actively investing in creating a digital experience for its consumers by offering a range of personalised digital services.

Relevant skills you have and the skills you will need to learn

If you are working in the industry, you are already equipped with a strong set of skills in programs and tools that are useful to the big data industry.

  • You have knowledge and experience in building and running software on the cloud, such as AWS, Azure and OpenStack
  • You know the processes involved in maintaining, supporting, troubleshooting and implementing communications networks, such as LAN, WAN, WLAN and MAN
  • You will have a strong grasp of the programming language relevant to one’s domain and experience in tools such as Chef and Ansible
  • You will possess good interpersonal skills to communicate intelligently with internal stakeholders and customers, clients and vendors. This is a mandatory skill for every data science professional aiming to pursue a career in big data

Although a telecommunication professional and a data scientist might have access to the same source of data, there are two different approaches to interpret the data. A data scientist will look for meaning and insights from the data collected; a telecommunications engineer will look at data to identify errors or inconsistencies. 

To transition smoothly into big data, telecommunication professionals need to adjust their mindset and look at data differently. Below are the skills and knowledge you will need to become a data science professional.

  • Data visualisation: modelling tools and technologies to provide insightful solutions to stakeholders
  • Advanced computing and programming in R, Python, Hadoop, OpenStack and Spark
  • Statistical techniques and an analytical mindset, which is crucial for every data scientist to make effective decisions

The career outlook for telecommunication professionals with data science skills

Telecommunication companies are recruiting data scientists more than ever. With an increased focus on customer experience and satisfaction, the industry is increasingly moving towards telecommunication data scientists to analyse the pool of data collected and provide insightful solutions to improve customers’ lifetime value, develop new products and increase customer retention. 

With the rise in competition among the big telcos, big data is going to play a major role in differentiating its service offerings. If you are thinking of upskilling with the skills of a data scientist, you are moving on the right path. All you need is the extra skills to launch your career in the most lucrative, evolving and valued job roles in the industry.

Will my overseas qualifications and experience help me work as a data scientist in Australia?

If you have work experience and qualifications in the telecommunications industry in Australia or overseas, you can transition into a career in data science. Being in the industry already gives you an upper hand over other professionals looking to switch to data science. Brush up on your skills and get hands-on training in data science and data analytics. 

You don’t need a degree or full-time work experience to get your foot in the door. If you can demonstrate your skills acquired through practical skills-focused certifications in data science, internships and projects, you are all set to kick-start your career as a data scientist. 

Get a head start on your new career. Enrol in one of Australia’s most in-demand and practical data science and artificial intelligence training programs at the Institute of Data. Learn more here about our program or schedule a call today.

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