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 jobsaverage 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.
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duties and responsibilities
As a data scientist, your daily work activities include:
- synthesising and analysing data: as a data scientist, you collect data from different sources in the company and analyse it. You collect data from various software programs and other business intelligence dashboards.
- developing forecast models: as a data scientist, you determine the statistical and analytical tools used to evaluate data in an organisation. You create predictive models and forecasts based on the information stipulated by the company.
- proposing hypotheses: from the initial data analysis, you present a hypothesis that solves a specific business problem. You use the hypothesis as the basis of your research, and your analysis focuses on validating it for key decision-makers in the company.
- identifying data and analysis needs: as a data scientist, you identify the valuable data that a business needs to drive research and improve business growth. You can develop data models for collecting information from business intelligence needs. You also design metrics for tracking and measuring business performance.
- building new models and analytical tools: as a business grows and develops new products, it requires new predictive models to aid its growth. Your job is to develop the models and help the company collect information on consumer reactions to its products.
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work environment
As a data scientist, you typically work in an office environment. You conduct most of your analysis using computers and other information technology. Your job may involve travelling to meetings or conferences, but regular travel is uncommon. You may not even work in a traditional office. Increasingly, many data scientists work remotely, either going into an office occasionally or working entirely online.
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who are your colleagues?
Depending on your employer and the industry you work in, your colleagues might include researchers, business analysts, finance analysts, data analysts, data engineers, chemical engineers and economists. You might also be working in close proximity to other specialists that could include, but not be limited to, project managers, research scientists, technical writers and data analysts.
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work schedule
The work schedule of a data scientist is relatively predictable. Most of the time, you work standard office hours on weekdays; late hours or weekend work are rare. However, flexibility in working hours is an expected part of the job. Delivering reports or similar publications is integral to many data scientists' roles, and late hours may be necessary when a deadline approaches. On average, you work between 37 and 39 hours a week.
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job outlook
Your career as a data scientist offers excellent prospects for advancement. In addition to going deeper into data science through experience and postgraduate study, you can move into other fields. You could specialise in data sciences like artificial intelligence or machine learning. If you enjoy working with large teams of data scientists, consider moving into a management role. If you're more focused on the science side of your work, entering academia as a researcher or lecturer may be for you.
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advantages of finding a data scientist job through randstad
Finding your data scientist job through Randstad provides important advantages such as:
- a wide variety of training and development opportunities
- an experienced contact person to provide help if needed
- a range of opportunities in your area
- get paid weekly or monthly, depending on the job
- temporary and permanent contracts
Want a permanent contract? A temporary job as a data scientist is often a stepping stone to an attractive permanent job. Every year, thousands of people earn a permanent contract with great employers thanks to a temporary job found through Randstad. What's more, many companies recruit their permanent employees through Randstad too.
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:
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is data scientist an easy job?
Data science is a rewarding career but requires work to build the necessary expertise. You use your expert data analysis and modelling knowledge to help corporates or government leaders make important decisions. Uncovering patterns in large data sets is challenging, and you need extensive education and work experience to accomplish your goals.
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is data science a good career?
If you have an analytical mind and enjoy using detailed knowledge to solve problems, being a data scientist is a great career. Working as a data scientist allows you to participate in groundbreaking inventions that improve business growth and people's lives. It also offers opportunities for advancement and the potential for high pay.
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do data scientists get paid well?
Data scientists have valuable skills and receive salaries that reflect their expertise. At the beginning of your career in data science, you could earn around $115,000 per year, moving up to $135,000 annually, or even more with extensive experience. Your salary may also increase based on your area of specialisation. If you participate in pharmaceutical research or artificial intelligence, you are likely to earn more than in other fields.
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what skills are needed to be a data scientist?
A data scientist needs a strong background in maths and data analysis. Familiarity with a range of software and programming languages is also beneficial. You require good problem-solving abilities since all research begins with identifying a problem and possible solutions. Your analytical mind helps you group data sets and form meaningful conclusions.
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is data science a good job for the future?
Data-driven decision-making is important for businesses, governments and academia. The need for data scientists is predicted to grow in an increasingly data-driven world. The projected job growth for data scientists is 27.7% in the next five years, making the career prospects promising.
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how do I apply for a data scientist vacancy?
Applying for a data scientist job is easy: create a Randstad profile and search our data scientist job offers. Then simply send us your CV and cover letter. Need help with your application? Check out all our job search tips here.
