what is a data scientist?
More than ever, companies, governments and other institutions rely on data to make decisions. This data can track traffic flows, consumer purchasing habits and weather patterns. Raw data doesn't help decision-makers choose the best options; someone has to process and analyse it. This task falls to data scientists as expert analysts with deep knowledge of technology and statistics.
Data scientists combine analytical skills with knowledge of the topic they're analysing to create models based on their study data. As a data scientist, you use these models to understand past and present situations and predict future behaviour.
what do data scientists do?
Like all scientists, data scientists conduct analyses and present their findings to stakeholders. Communication skills are a vital part of your job as a data scientist. You provide clear, useful information when communicating with corporate management, the government or the public.
As a data scientist, your knowledge benefits government institutions and non-government organisations that sponsor research in various fields. Some data scientists work in the healthcare, pharmaceutical and chemical industries. You can also work for mining, automobile and meteorology companies. You contribute to agriculture and mining by predicting natural disasters and other events that affect these sectors.data scientist jobs
average salary of a data scientist
Due to the rising demand for data scientists, the remuneration package is usually competitive, even for beginners. The average remuneration for data scientists in Australia is $125,000 annually. At entry-level, joining the field with minimal experience, your starting salary is $115,000 per year. The amount increases as you build your skills or specialise in specific sectors. An experienced data scientist takes home over $135,000 per year. The remuneration package includes annual leave days and paid sick days, among other benefits.
what factors affect the salary of a data scientist
The salary of a data scientist is based on expertise and qualifications. Entry-level data scientists are likely to earn less due to their minimal experience. When you have additional qualifications, your earnings increase steadily. The size of the project and the funding also influences your salary. Some projects have limited resources and pay less than large projects with higher budgets.
Working for the private sector also increases your remuneration prospects compared to working for the government. Evaluate the monetary and non-monetary benefits you are likely to receive before signing a contract.
Want to know what you will earn as a data scientist? Check out what you are worth with our salary checker.
types of data scientists
In the world of data science, you can pursue different specialisations. These include:
- data engineering: as a data engineer, you build and maintain the frameworks used for analysis by consolidating, cleaning and structuring data collected from multiple sources.
- database management and architecture: a step up from a data engineer, this specialist is responsible for designing an organisation's digital framework.
- operations data analysis: as an operations data analyst, you work in a less technical role using statistical software to evaluate and solve business-specific problems.
- marketing data analysis: as a marketing data analyst, you are concerned with measuring and improving the effectiveness of a marketing campaign, particularly in terms of ROI and considering marketing trends.
- machine learning: machine learning is a growing field within data science. Data scientists specialising in machine learning create algorithms without direct human participation. These automated systems can operate many times faster than humans, making them ideal for large data sets.
- artificial intelligence: artificial intelligence (AI) is another specialisation area within data science. Although related to machine learning, AI has its methods and principles, and many data scientists specialise in one or the other.
working as a data scientist
Working as a data scientist is an exciting career that allows you to contribute to solving a range of problems. Read on to find out what data scientists do daily, their work environments and their schedules.
education and skills
To land a job as a data scientist in Australia, you require a postgraduate qualification in data science. Other educational qualifications include:
- bachelor's degree: to qualify as a data scientist, pursue a bachelor's degree in relevant fields like mathematics, computer science, IT and statistics. The bachelor's degree takes three years, and you can study for a postgraduate qualification after completing it. A graduate diploma or master's in data science improves your skills.
- work experience: when you complete the courses, secure an internship or start as an entry-level data analyst to gain work experience in the role.
skills and competencies
Some of the skills and competencies of a data scientist include:
- maths and statistics: as a data scientist, you make data predictions based on your analysis. Since you deal with large amounts of data, you require mathematical skills and proficiency in using statistical tools to predict trends from the data.
- communication skills: your communication skills enable you to present and explain findings to stakeholders. Using appropriate language to summarise the research process helps non-specialists to understand your results.
- analytical skills: you rely on data analysis to make conclusions and help businesses with decision-making. Analytical thinking enables you to resolve complex data problems.
- programming: as a data scientist, your job may involve developing software and statistical models for analysis. Programming skills are crucial for writing the codes and creating predictive models.
FAQs about working as a data scientist
Here are the most asked questions about working as a data scientist: