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The exponential growth of digital services has led to the development of the data science industry, which is responsible for the analysis, modelling, and visualisation of data. In fact, it is also highlighted as a primary growth area in the SkillsFuture 2023 Report. Moreover, it’s a highly sought-after skill by businesses aiming to refine their operations and make informed decisions. The lack of data scientists, which is used as an umbrella term to encompass various data science-related roles in the market, has led to lucrative salary offers for these professionals. If you’re considering a career as a data scientist, here’s how much you can earn in Singapore. A data scientist is an analytical professional who’s responsible for designing and implementing processes and logic to extract, transform, and load data from multiple data sources to obtain business insights and recommendations. It requires a combination of conventional and technological skillsets such as mathematics, advanced statistical analysis, machine learning techniques, and predictive modelling. Depending on the industry they are in, a data scientist may also be referred to as a data analyst, data architect, data engineer, or statistician. Based on tech-talent platform NodeFlair’s 2024 report, salaries for data scientists increased by 11.3% year-on-year. Based on the same report’s findings, the median monthly salary for a junior data scientist is $7,500. On the other hand, a Lead data scientist, who might be managing a small team of data scientists, could earn as much as $17,000 per month.   The higher salaries for data scientists are due to the demand for their advanced analytical skills and the complexity of their work. As a data scientist, you would be required to perform some of the following job functions based on your industry and experience: Being a data scientist requires a wide range of complex planning, analysis, and modelling. To ensure candidates are able to perform this role, most companies would require at least a bachelor’s degree in the following fields: business analytics, computer engineering, computer science, data analytics, engineering, information technology, information systems, mathematics, or statistics. In some instances, you may be required to possess post-graduate qualifications in data science or computer science if you have bachelors in unrelated fields. Another way to become a data scientist is to have relevant professional certification or boot camp experience. This could mean taking up the required technical skillsets or gaining project experience in order to perform the job functions as a data scientist. As a data scientist, you will need to evaluate large amounts of unorganised and freeform data. This requires various technical and non-technical skillsets. Here’s a detailed look at the key skills that you’ll need: : In order to sort through, analyse, and manage large amounts of data, you would be required to know programming languages such as the following: : Tools like Tableau, PowerBI, and Excel help data scientists translate information and data into visuals like 3D plots, relationship maps, histograms, bar charts, and line plots. These data visualisation tools help data scientists spot trends, patterns, and outliers in a set data. : Having an in-depth knowledge of techniques such as supervised machine learning, unsupervised machine learning, reinforcement learning, decision trees, and neural networks could be useful for a data scientist. : As part of managing big data, data scientists also need to handle unstructured data (text, images, and audio) using techniques like natural language processing (NLP) and computer vision. In addition to the technical skills, you’ll also need the following non-technical skills: Based on NodeFlair’s 2024 report, the top 15 searched Singapore-based companies for tech roles are: Among these companies, the FAANGs—Meta, Apple, Google—generally around 30% to 50% more than the median. Beyond the well-established companies in the IT and banking sectors, there are many startups in the data science field, like Crayon Data and Tookitaki, where there might be job opportunities for data scientists. Demand for data scientists is expected to grow in the coming years, given the country’s push towards being a Smart Nation as it positions itself as a technological hub, attracting both tech startups and big tech companies. While being a data scientist requires continuous learning, curiosity, and skill development, the ever-changing technological landscape could potentially present exciting opportunities and challenges that could make for a rewarding career if you’re able to overcome its complexities.