Career Development in Data Analytics

Recently, I had an opportunity to share insights about data analytics career opportunities in Singapore at WSG Adapt & Grow ICT Event organized by Singapore Computer Society and Workforce Singapore (WSG).

Due to my everyday work, am lucky to have information about Singapore ICT candidates seeking career opportunities and about ICT talent demand of organizations, and I have access to relevant data and tools to analyse the demand of tech skills in Singapore. And I shall like to share some of my observations with you about career development in data analytics.
Almost all sectors of the economy are using or plan to use analytics. And with the government planning to make Singapore a Big Data hub in Asia, and with the continued development of Singapore’s startup ecosystem, demand for analytics skills is expected to keep increasing.

The data analytics career opportunities are available across the industries as shown below.

Across the industries, the four areas in which analytics is being used significantly are Customer Analytics, Operations Analytics, Risk Analytics and HR Analytics.

If you are seeking career opportunities within data analytics or trying to switch career to data analytics or trying to start a career within data analytics, you may like to keep the following tips in your mind:

1. Business process knowledge is valuable: Based on our observations, one of the key success factors in analytics to get relevant insights, is the business process knowledge. And this can create opportunities for qualified professionals who have a good understanding of business domain. We invariably notice that the business knowledge is either ignored or understated by qualified professionals. They can highlight their business domain knowledge when they apply for any data analytics career opportunities.

2. Understand the role before positioning yourself: Secondly, before one applies for any role within data analytics, one must understand the role and the stage of analytics project life cycle in which you shall be adding value. Below is the illustration of the end-to-end life cycle of a typical analytics project.

3. Go-to strategy: Based on the self-assessment, one can enter into data analytics arena from any of the following backgrounds:

• Technology (e.g. Developer, Data Engineer)
• Industry/Business Process (e.g. Business Analyst, Data Analyst)
• Applied Statistics (e.g. Statistician or Mathematician)

Once you are a member of data analytics project, you can start learning about other areas. Mostly, professionals specialize in one or two of the above areas.

4. Know the hot skills: Based on our insight, following skills are in high demand and one can strengthen his/her expertise in these technologies:

• Python: Python is very widely used at the moment, and demand for this skill is expected to keep growing. Current general sentiment around it is 80% positive.
• SAS: SAS has a significant base already, particularly in the corporate sector. Demand for it is expected to continue to grow in the foreseeable future. Current general sentiment around it is 83% positive.
• Tableau: Tableau also has a significant base and is expected to continue to grow in the foreseeable future. Current general sentiment around it is 88% positive.
• Hadoop: Hadoop is widely used in Big Data and its use is expected to continue to grow in the foreseeable future. Current general sentiment around it is 81% positive.
• QlikView: Qlikview has a very large user base now and demand for this skill is also expected to continue to grow in the foreseeable future. Current general sentiment around it is 88% positive.

The complete view of all the skills being sought by employers in Singapore within data analytics is:

• Data Science: linear algebra, statistics, econometrics, computer science, operations research, NLP, image processing, machine learning, deep learning
• Functional: strategy, risk, sales and marketing, financial, HR, operational, quality, etc.
• Sectoral: financial services, energy, retail, telecom, etc.
• Technology (around large databases and data delivery): BI, big data (Hadoop, Storm, Kafka, Cassandra, Spark, Hive, Pig), cloud computing, security, visual modelling and design, languages such as Java, Python, Julia, Scala, R, etc.
• Tools: SPSS, SAS, RStudio, Flare, HighCharts, QlikView, Tableau, etc.
• Soft Skills: communication, cross-functional perspective, teamwork and interpersonal skills, creativity, analytical thinking, discipline

If you already have knowledge or experience in any of the above areas/technologies/tools then you should try to build your expertise in it.

5. Write a winning resume: Keeping the above information in mind, try to elaborate the relevant experience, skills/expertise in your resume based on the requirement of a job description. Invariably, we notice that the resumes are written using standard templates with one fits all approach and experienced professionals miss out the relevant information for the specific job requirement. Customize a winning resume and apply for only the most relevant job roles within the targeted industry.

6. Prepare well before an interview: Once an interview opportunity comes by, you must prepare well. Understand the job description well. If possible, speak to recruitment consultant or talent acquisition executive to know more about the project background and role expectations. Recall your past relevant experience. MyTechLogy also offers interview guidance tool for most of the ICT roles. Each role has specific needs of capabilities which you must be aware of. MyTechLogy provides you sample interview questions for each capability along with interview tips to help ICT professionals succeed.

Demand for data analytics skills is expected to continue to grow for the next several years. In the short to medium term, the skills shortage is likely to continue, and that presents an excellent and rewarding career opportunity for data analytics aspirants in Singapore.