Australia data scientist salary

Australia data scientist salary DEFAULT

Data Scientist Salary in India – For Freshers &#; Experienced


Data science is a field that combines domain knowledge, programming abilities, and mathematics and statistics knowledge to extract useful insights from data. Machine learning algorithms are used to number, text, photos, video, audio, and other data to create artificial intelligence (AI) systems that can execute jobs that would normally need human intelligence. As a result, these systems produce insights that analysts and business users may employ to create meaningful commercial value.

Data Science Workflow

Capturing data, occasionally extracting it, and entering it into the system is the first stage of the data science pipeline workflow. Data warehousing, data cleansing, data processing, data staging, and data architecture are all included in the maintenance stage.

Following that, data processing is one of the cornerstones of data science. Data scientists are distinguished from data engineers throughout the investigation and processing of data. The procedures that create useful data include data mining, data categorization and clustering, data modeling, and summarising insights obtained from the data.

The next stage is data analysis, which is equally important. Data scientists work here on exploratory and confirmatory work, regression, predictive analysis, qualitative analysis, and text mining, among other things. When done correctly, there is no such thing as cookie-cutter data science at this stage.

The data scientist shares insights during the last stage. Data visualization, data reporting, the use of various business intelligence tools, and supporting organizations, policymakers, and others in making better decisions are all part of this.

Data Science Program

In this article, we will be covering what a data scientist is and their roles and responsibilities. We will furthermore discuss what are the reasons to become data scientists, the skills required for becoming a data scientist, their salary in India and abroad, what are the factors that determine their salary, what are the top companies hiring data scientists, and the challenges to overcome in a data science career and some of the FAQs asked by the people.

Who is a Data Scientist and What do they do?

Data scientists acquire and analyse enormous sets of organised and unstructured data. A data scientist&#;s job entails a mix of computer science, statistics, and mathematics. They interpret the outcomes of data analysis, processing, and modelling to generate actionable plans for businesses and other organisations.

Data scientists are analytic professionals that use their knowledge of technology and social science to identify patterns and handle data. They identify solutions to corporate difficulties by combining industry knowledge, contextual insight, and scepticism of established assumptions.

As a result, data scientists are a mix of computer scientists, mathematicians, and trend analysts. Data scientist salaries in India are among the highest due to great demand.

A data scientist&#;s job entails deciphering complex, unstructured data from sources like smart devices, social media feeds, and emails that don&#;t fit neatly into a database.

Data Scientist Salary in India

The average salary for a data scientist is Rs, per year. With less than a year of experience, an entry-level data scientist can make approximately , per year. Data scientists with 1 to 4 years of experience may expect to earn about , per year.

average salary of data scientist in india
average salary of data scientist in IT sector india
graph of data scientist salary in india

Skills Required for a Data Scientist

  • Algorithms, statistics, mathematics, and machine learning knowledge are all important.
  • R, Python, SQL, SAS, and Hive are examples of programming languages that are required to be known by a Data Scientist.
  • Communication skills are required in order to properly communicate the results to the rest of the team.

Data Scientists Job Roles and Responsibilities

Data Scientists Job Roles

Data scientists work closely with business stakeholders to learn about their objectives and how data may help them achieve goals. They create algorithms and predictive models to extract the data that the business needs, as well as help evaluate the data and share findings with peers. Along with R, Python has demonstrated its ability to sort data according to both generic and specialized needs. Python data science programmers in India make higher than both software developers and DevOps programmers. The reason for this is that data gathering, data cleansing, and data processing are becoming increasingly popular in today&#;s world, as businesses require data to obtain market and customer data.

Data Scientists Responsibilities

  • Taking massive amounts of structured and unstructured data and turning it into useful information.
  • Identifying the data-analytics solutions that have the most potential to propel businesses forward.
  • Using data analysis tools such as text analytics, machine learning, and deep learning to uncover hidden patterns and trends.
  • Data cleansing and validation to improve data accuracy and efficacy.
  • Data visualization is used to communicate all of the positive observations and discoveries to the company&#;s stakeholders.

Key Reasons to Become a Data Scientist

1. Growing Demand

One of the most in-demand jobs for is data science. Data science and analytics are expected to employ more than 11 million people by India is the second-largest source of data scientist jobs after the United States. One of the main reasons for the high salaries of data scientists in India is the high demand.

2. High-paying jobs with a wide range of responsibilities

Not only is there a high demand for data scientists, but the types of jobs available are also plentiful. The demand for data scientists is rapidly increasing, and there is a substantial supply shortage. Due to a shortage of essential skill sets, there are a large number of vacant job openings all around the world. Because of the severe scarcity of talent, this is an excellent time to enter this sector.

3. Changing working environments

The future workplace is being shaped by data science. More and more routine and manual chores are being mechanized thanks to artificial intelligence and robotics. As people take on more critical thinking and problem-solving roles, data science technologies have made it easier to educate robots to perform repetitive jobs.

4. Increasing product quality

Machine learning  and Artificial Intelligence has allowed businesses to personalize their offers and improve client experiences. They are thriving in every industry, from information technology to health care, and from e-commerce to marketing and retail. Because data is a company&#;s most valuable asset, Data Scientists play a critical role as trusted advisers and strategic partners to management. They look for relevant information in the data that might help them improve their specialty, determine their desired target audience, and plan future marketing and growth initiatives.

5. Contributing to the greater good

The healthcare industry has been transformed by predictive analytics and machine learning. Early diagnosis of cancers, organ defects, and other diseases is possible because of data science.

6. Evolving Field

Because of the growing demand for data all around the world, data science is rapidly evolving. Data scientists have a wide range of skills that may help firms make better strategic decisions by leveraging data and information. They have great possibilities to engage with data and experiment to find the best solutions for organisations. Big Data, Artificial Intelligence (AI), Machine Learning (ML), as well as some newer technologies like Blockchain, Edge Computing, Serverless Computing, Digital Twins, and others that employ various practises and techniques within the Data Science industry, are just a few of the new exciting fields that are emerging within this field.

 7. Interesting Job role

Human behaviour is the primary focus of data scientists. As a data scientist, you&#;ll largely be working on how humans operate, from designing a chatbot to evaluating user experience online. As a result, you&#;ll be directly participating in one of the century&#;s most important endeavours.

8. Extensive job experience

You can experiment with a wide range of fields as a data scientist. You&#;ll be able to work on a variety of geeky projects, ranging from ecommerce enterprises to startups to production companies to renewable energies to traffic optimization. As a result, you&#;ll have a lot of &#;horizontal mobility&#; in the field.

Data Scientist Salary Deciding Factors

Based on Experience

Let&#;s look at how the salary of a Data Scientist in India differs based on experience.

data scientist salary in india by experience

Because of the strong association between years of work experience and higher-paying salaries, a career in data is particularly appealing to young IT workers. We&#;ll look at how data scientist salaries rise with experience in this section. In the future, salaries in the field of data may look something like this:

In India, the average entry-level data scientist income is , rupees per annum for a recent graduate.

entry level data scientist salary in india

A data scientist in their early career with years of experience earns an average of Rs, per year.

early level data scientist salary in india

Employees with 5 to 9 years of experience can expect to earn between INR 12 and 14 lakhs per annum. The average mid-level data scientist income, according to payscale, is Rs1,, per annum

mid level data scientist salary in india


A highly experienced employee with decades of expertise or who has held management positions might expect to earn anywhere from INR 24 lakhs per annum to a healthy crore!

With a transition/promotion from the role assigned to them to a higher one, a data analyst&#;s income improves by 50%.

Based on Location

Mumbai has the most job prospects and the highest yearly data scientist salaries in India for data innovators, followed by Bangalore and New Delhi. However, because Bangalore is India&#;s startup capital, it boasts the most startup job opportunities. Because Bangalore is considered the centre of India&#;s tech industry, a data scientist&#;s compensation is likely to be higher than in other locations.

According to Payscale, a data scientist&#;s income in India varies depending on where they work:

Mumbai Rs, per annum
Chennai Rs, per annum
Bangalore Rs, per annum
Hyderabad Rs, per annum
Pune Rs, per annum
Kolkata Rs. , per annum

Source: Payscale

Bangalore, Chennai, and Hyderabad are three of the highest paying cities for data scientists in India.

Based on Employer

Without a doubt, prominent organisations are at the top of the list of the highest-paying data positions. They also have a reputation for raising salaries by 15% per year. Top firms pay data scientists in the following ways:

IBM Corp INR 1,, per annum
Accenture INR 1,, per annum
JP Morgan Chase and Co INR , per annum
American Express INR 1,, per annum
McKinsey and Company INR 1,, per annum
Wipro Technology INR 1,, per annum

Based On Skills

To get a job paying this well, you&#;ll need to have more than a Master&#;s degree and be conversant with the languages and tools used to manage data. Here are some additional AIM tidbits:

  • Knowing R is the most crucial and sought-after expertise, followed by Python. Python salary in India is expected to be around lakhs INR per annum
  • When a Data Analyst has knowledge of both Big Data and Data Science, their income rises by 26%, compared to when they only have knowledge of one.
  • SAS users are paid in the range of INR lakhs per annum, whereas SPSS professionals are compensated in the range of INR lakhs per annum.
  • Machine Learning salaries in India start at roughly lakhs INR and can rise to 16 lakhs INR as you advance in the industry. Python is one of the most popular languages for machine learning, and Python developers in India earn some of the best salaries in the world.
  • Artificial Intelligence knowledge can assist to advance your career in general. If you are a beginner in this field, the Artificial Intelligence pay in India is not less than lakhs INR.

So now is the time to improve data abilities in order to maximize your earnings!

Top Companies Who Hire Data Scientist

Mu Sigma, Accenture, and Tata Consultancy Services Limited are the top respondents for the job title Data Scientist in India. Inc has the highest reported salaries. Accenture and HCL Technologies Ltd. are two more firms that pay well for this position. Mu Sigma pays the least. Tata Consultancy Services Limited and IBM India Private Limited are likewise on the low end of the range.

Data Scientist Salary in Other Countries

Salaries offered by the top 5 countries are as follows-

United States

The United States of America is at the top of the list of countries that give high salaries to data scientists who are willing to work for them. The average yearly salary for data scientists in the United States is $, per year. The pay is higher than in any other country for data scientists.


Australia is ranked second in the list of countries that pay data scientists well. This is evidenced by the influx of data scientists from Australia and other countries to the United States. The average salary for a Data Scientist is between AU$75, per year- AU$, per year based on one’s experience.


Nobody could have predicted that Israel would become a major IT centre, with a plethora of career opportunities for both novice and seasoned data scientists. In Tel Aviv, Israel, working data professionals earn roughly $88, per year


You&#;re in for a treat if you&#;re seeking data science employment in Canada. Data scientists in Canada make roughly $81, per year. The starting wage for a data scientist is $77, per year and can rise to $, per year.


In Germany, people looking for data science employment might earn up to 5, euros per month. Working data scientists in Germany earn between 2, and 9, euros per month.

Challenges to Overcome in Data Science Career

1). Preparation of Data

Before using data for analysis, data scientists spend roughly 80% of their time cleaning and preparing information to improve its quality – that is, to make it accurate and consistent. However, 57 percent of them regard it to be the most difficult aspect of their professions, describing it as time-consuming and monotonous. On a daily basis, they must process terabytes of data across numerous formats, sources, functions, and platforms while keeping a track of their activities to avoid repetition.

Adopting developing AI-enabled data science solutions like Augmented Analytics and Auto feature engineering is one way to address this problem. Data scientists can be more productive by using Augmented Analytics to automate tedious data cleansing and preparation chores.

2) A variety of data sources

More data sources will be needed by data scientists to make meaningful judgments as firms continue to use various sorts of apps and technologies and generate various formats of data. This approach necessitates manual data entry and time-consuming data searching, which results in errors, repetitions, and, ultimately, incorrect conclusions.

To rapidly access information from many sources, organisations require a single platform that is integrated with different data sources.Data in this unified platform can be pooled and regulated effectively and in real-time, allowing data scientists to save a significant amount of time and effort.

3) Data Protection

Cyberattacks are becoming more widespread as firms migrate to cloud data management. This has resulted in two key issues:

  • Confidential information is at risk.
  • As a result of recurrent cyberattacks, regulatory norms have grown, lengthening the data consent and utilisation processes, further aggravating the data scientists&#; displeasure.

To protect their data, businesses should use powerful machine learning-enabled security platforms and implement additional security measures. Simultaneously, they must maintain rigorous adherence to data protection regulations in order to prevent time-consuming audits and costly fines.

4) Recognizing the Business Issue

Data scientists must first completely understand the business challenge before undertaking data analysis and developing solutions. Most data scientists take a mechanical approach to this, jumping right into examining data sets without first identifying the business problem and goal.

As a result, before beginning any analysis, data scientists must follow a specific methodology. The workflow should be created after consulting with business stakeholders and include well-defined checklists to aid in problem identification and understanding.

5) Effective Non-Technical Stakeholder Communication

Data scientists must be able to communicate successfully with corporate leaders who may not be aware of the complexity and technical language involved in their work. If the CEO, stakeholder, or client is unable to comprehend their models, their solutions are unlikely to be implemented.

This is a skill that data scientists can develop. They can use concepts like &#;data storytelling&#; to provide their communication a more systematic approach and a compelling narrative to their analyses and visuals.

6) Metrics and KPIs That Aren&#;t Defined

Management teams&#; lack of awareness of data science leads to unrealistic expectations of data scientists, which has an impact on their performance. Data scientists are supposed to come up with a magic bullet that will solve all of the company&#;s problems. This is quite ineffective.

As a result, every company should have:

Data scientists must use well-defined metrics to assess the accuracy of their analyses.

Appropriate business KPIs to assess the impact of the analysis on the business.


Despite the difficulties, data scientists are the most sought-after experts in the industry. With the data world developing at such a rapid rate, being a successful data scientist requires not only technical capabilities but also a thorough understanding of business requirements, collaboration with various stakeholders, and persuasion of business executives to act on the information offered.


1. Do I need a degree to become a Data Scientist?

There are no degrees that will qualify you as a trustworthy data scientist.

There are no prerequisites for becoming a credible data scientist, but neither are there any prerequisites for becoming a credible data scientist.

Unlike several other occupational titles, “data scientist” is not a protected title. Medical doctors, nurses, and lawyers, for example, have stringent requirements. Data science, however, does not.

Data science has a wide range of applications and is fundamentally interdisciplinary. As a result, education is still relevant. Data scientists come from a variety of educational backgrounds.

Computer related fields and Statistics are the two most generally advised degrees if you wish to pursue data science as a career. However, all STEM degrees are useful. Obtain a bachelor&#;s degree in information technology, computer science, mathematics, physics, or a related discipline; Obtain a master&#;s degree in data science or a closely related discipline; Obtain experience in the field in which you wish to work (ex: healthcare, physics, business).

2. How much money can you make in data science?

The average data scientist salary in India is Rs. , With less than a year of experience, an entry-level data scientist can make approximately Rs. , per year. Data scientists with 1 to 4 years of experience may expect to earn about Rs. , per year. In India, a mid-level data scientist with 5 to 9 years of experience earns Rs.1,, Senior-level data scientists in India earn roughly 1,, per year as their expertise and talents increase.

 3. Are Data scientists highest paying jobs?

One of the highest-paying careers is data science. Data Scientists earn an average of Rs, a year, according to Glassdoor. As a result, Data Science is a very lucrative career choice.

In , there are expected to be million open positions in data analysis, data science, and related fields (source: IBM). Employer demand for both data scientists and data engineers is expected to climb by 39% by

4. Is Data Scientists a good career?

Data Scientists is A “Lucrative Career”.

In recent years, the input of data has increased at an exponential rate. As massive amounts of data began to flow into data centres, numerous new opportunities arose, particularly in data science. Digital transformation was the only option due to technological advancements in the data landscape. As more businesses embrace digitisation, they are looking for employees to fill data science and related positions. Data science professionals are in high demand all across the world. These job prospects are likely to increase significantly beyond , with more than lakh additional jobs being created. Glassdoor has ranked data science as the number one job in the United States for the past four years, hence it is a good career option.

5. Can I become a data scientist with no experience?

Data science is a booming area, and many people may be considering a career change due to lucrative work opportunities. You must, however, be able to explain your professional change. You may become a data scientist without any prior experience if you keep these things in mind.

To become a data scientist, follow these three steps: Obtain a bachelor&#;s degree in information technology, computer science, mathematics, physics, or a related discipline; Obtain a master&#;s degree in data science or a closely related discipline; Obtain experience in the field in which you wish to work (ex: healthcare, physics, business).

6. Can I become data scientists without a Masters?

While some schools are offering or developing Masters Programs with this title, the majority of Data Scientists today do not hold such a degree. There are numerous options for doing so, both with and without an advanced degree programme. Many people are performing excellent &#;Data Science&#; work under different names.

7. Can I learn data science without Programming?

One of the most difficult and popular disciplines of computer science is data science. Before learning Python, you&#;ll need to understand some basic data science ideas, after which you&#;ll be able to solve a variety of real-world problems without writing a single line of code!

While programming is undoubtedly a necessary ability for a data scientist profession, this does not imply that you must be an avid programmer to pursue a career in data science. Being a good coder is a highly desirable but not required talent for a data scientist.

8. Data Scientist Salary in US?

The United States of America is at the top of the list of countries that give high salaries to data scientists who are willing to work for them. The average yearly salary for data scientists in the United States is $, per year. The pay is higher than in any other country for data scientists.

Additional Resources


Data Scientist

What's it like to be a Data Scientist?

Data Scientists look for patterns in large amounts of raw data and use the data to identify trends and patterns that will help provide insights into, or solve, real-world problems.

Data Scientist

Tasks and duties

  • Determining question/s that need to be answered by developing hypotheses, gathering, organising and cleaning raw data.
  • Applying algorithms in order to explore, analyse and interpret patterns in the data.
  • Creating data-driven solutions for identified problems and issues, and communicating the results to a wide variety of personnel and stakeholders.

Read less

Data Scientists are employed in a range of fields, including finance, IT, public administration, health and retail.

Data Scientists need to have strong technical skills and be confident with programing in a variety of languages such as R, python, SQL and SAS. Successful Data Scientists are analytical individuals who have strong mathematical abilities, in addition to excellent communication skills.

  1. Macklin font
  2. G flat ukulele
  3. Mark henry ryback

Data Scientist Average Salary in Australia

How much money does a Data Scientist make in Australia?

Average Yearly Salary


( 12, AUD monthly)


A person working as a Data Scientist in Australia typically earns around , AUD per year. Salaries range from 77, AUD (lowest) to , AUD (highest).

This is the average yearly salary including housing, transport, and other benefits. Data Scientist salaries vary drastically based on experience, skills, gender, or location. Below you will find a detailed breakdown based on many different criteria.

Data Scientist Salary Distribution in Australia

Median and salary distribution yearly Australia Data Scientist
Share This Chart  Tweet      Get Chart Link

The median, the maximum, the minimum, and the range

  • Salary Range

    Data Scientist salaries in Australia range from 77, AUD per year (minimum salary) to , AUD per year (maximum salary).

  • Median Salary

    The median salary is , AUD per year, which means that half (50%) of people working as Data Scientist(s) are earning less than , AUD while the other half are earning more than , AUD. The median represents the middle salary value. Generally speaking, you would want to be on the right side of the graph with the group earning more than the median salary.

  • Percentiles

    Closely related to the median are two values: the 25th and the 75th percentiles. Reading from the salary distribution diagram, 25% of Data Scientist(s) are earning less than 96, AUD while 75% of them are earning more than 96, AUD. Also from the diagram, 75% of Data Scientist(s) are earning less than , AUD while 25% are earning more than , AUD.

What is the difference between the median and the average salary?

Both are indicators. If your salary is higher than both of the average and the median then you are doing very well. If your salary is lower than both, then many people are earning more than you and there is plenty of room for improvement. If your wage is between the average and the median, then things can be a bit complicated. We wrote a guide to explain all about the different scenarios. How to compare your salary

Data Scientist Salary Comparison by Years of Experience

How does experience and age affect your pay?

Salary comparison by years of experience yearly Australia Data Scientist
Share This Chart  Tweet      Get Chart Link

The experience level is the most important factor in determining the salary. Naturally the more years of experience the higher your wage. We broke down Data Scientist salaries by experience level and this is what we found.

A Data Scientist with less than two years of experience makes approximately 89, AUD per year.

While someone with an experience level between two and five years is expected to earn , AUD per year, 23% more than someone with less than two year&#;s experience.

Moving forward, an experience level between five and ten years lands a salary of , AUD per year, 42% more than someone with two to five years of experience.

“On average, a person&#;s salary doubles their starting salary by the time they cross the 10 years* experience mark. ”

Additionally, Data Scientist(s) whose expertise span anywhere between ten and fifteen years get a salary equivalent to , AUD per year, 17% more than someone with five to ten years of experience.

If the experience level is between fifteen and twenty years, then the expected wage is , AUD per year, 10% more than someone with ten to fifteen years of experience.

Lastly, employees with more than twenty years of professional experience get a salary of , AUD per year, 6% more than people with fifteen to twenty years of experience.

Data Scientist average salary change by experience in Australia

0 - 2 Years

89, AUD

2 - 5 Years+23%


5 - 10 Years+42%


10 - 15 Years+17%


15 - 20 Years+10%


20+ Years+6%


Percentage increase and decrease are relative to the previous value

Typical Salary Progress for Most Careers

Salary Comparison By Experience Level
Share This Chart  Tweet      Get Chart Link

Data Scientist Salary Comparison By Education

How do education levels affect salaries?

Displayed below is the average salary difference between different Data Scientist(s) who have the same experience but different education levels.

Salary comparison by education level yearly Australia Data Scientist
Share This Chart  Tweet      Get Chart Link

We all know that higher education equals a bigger salary, but how much more money can a degree add to your income? We broke down Data Scientist salaries by education level in order to make a comparison.

When the education level is Bachelor&#;s Degree, the average salary of a Data Scientist is 98, AUD per year.

While someone with a Master&#;s Degree gets a salary of , AUD per year, 59% more than someone having a Bachelor&#;s Degree degree.

A PhD gets its holder an average salary of , AUD per year, 30% more than someone with a Master&#;s Degree.

Data Scientist average salary difference by education level in Australia

Bachelor&#;s Degree

98, AUD

Master&#;s Degree+59%




Percentage increase and decrease are relative to the previous value

Is a Master&#;s degree or an MBA worth it? Should you pursue higher education?

A Master&#;s degree program or any post-graduate program in Australia costs anywhere from 37, Australian Dollar(s) to , Australian Dollar(s) and lasts approximately two years. That is quite an investment.

You can&#;t really expect any salary increases during the study period, assuming you already have a job. In most cases, a salary review is conducted once education is completed and the degree has been attained.

Many people pursue higher education as a tactic to switch into a higher paying job. The numbers seem to support the thoery. The average increase in compensation while changing jobs is approximately 10% more than the customary salary increment.

If you can afford the costs of higher education, the return on investment is definitely worth it. You should be able to recover the costs in roughly a year or so.

Typical Salary Difference by Education for Most Careers

Salary Comparison By Education Level
Share This Chart  Tweet      Get Chart Link

Data Scientist Salary Comparison By Gender

Salary comparison by gender yearly Australia Data Scientist
Share This Chart  Tweet      Get Chart Link

Though gender should not have an effect on pay, in reality, it does. So who gets paid more: men or women? Male Data Scientist employees in Australia earn 6% more than their female counterparts on average.





Percentage increase and decrease are relative to the previous value

Salary Comparison By Gender in Australia for all Careers

Salary comparison by gender yearly Australia
Share This Chart  Tweet      Get Chart Link

Data Scientist Average Annual Salary Increment Percentage in Australia

How much are annual salary increments in Australia for Data Scientist(s)? How often do employees get salary raises?

Data Scientist

Data Scientist(s) in Australia are likely to observe a salary increase of approximately 12% every 16 months. The national average annual increment for all professions combined is 8% granted to employees every 16 months.

Annual Salary Increment Rate Australia Data Scientist
Share This Chart  Tweet      Get Chart Link

The figures provided here are averages of numbers. Those figures should be taken as general guidelines. Salary increments will vary from person to person and depend on many factors, but your performance and contribution to the success of the organization remain the most important factors in determining how much and how often you will be granted a raise.

Australia / All Professions

The term &#;Annual Salary Increase&#; usually refers to the increase in 12 calendar month period, but because it is rarely that people get their salaries reviewed exactly on the one year mark, it is more meaningful to know the frequency and the rate at the time of the increase.

How to calculate the salary increment percentage?

The annual salary Increase in a calendar year (12 months) can be easily calculated as follows: Annual Salary Increase = Increase Rate x 12 ÷ Increase Frequency

“The average salary increase in one year (12 months) in Australia is 6%.”

Annual Increment Rate By Industry





Information Technology










Listed above are the average annual increase rates for each industry in Australia for the year Companies within thriving industries tend to provide higher and more frequent raises. Exceptions do exist, but generally speaking, the situation of any company is closely related to the economic situation in the country or region. These figures tend to change frequently.

Worldwide Salary Raises: All Countries and All Jobs

Share This Chart  Tweet      Get Chart Link

Data Scientist Bonus and Incentive Rates in Australia

How much and how often are bonuses being awarded?Annual Salary Bonus Rate Australia Data Scientist
Share This Chart  Tweet      Get Chart Link

A Data Scientist is considered to be a moderate bonus-based job due to the generally limited involvement in direct revenue generation, with exceptions of course. The people who get the highest bonuses are usually somehow involved in the revenue generation cycle.

45% of surveyed staff reported that they haven&#;t received any bonuses or incentives in the previous year while 55% said that they received at least one form of monetary bonus.

Those who got bonuses reported rates ranging from 3% to 5% of their annual salary.

Received Bonus


No Bonus


Types of Bonuses Considered

Individual Performance-Based Bonuses

The most standard form of bonus where the employee is awarded based on their exceptional performance.

Company Performance Bonuses

Occasionally, some companies like to celebrate excess earnings and profits with their staff collectively in the form of bonuses that are granted to everyone. The amount of the bonus will probably be different from person to person depending on their role within the organization.

Goal-Based Bonuses

Granted upon achieving an important goal or milestone.

Holiday / End of Year Bonuses

These types of bonuses are given without a reason and usually resemble an appreciation token.

Bonuses Are Not Commissions!

People tend to confuse bonuses with commissions. A commission is a prefixed rate at which someone gets paid for items sold or deals completed while a bonus is in most cases arbitrary and unplanned.

What makes a position worthy of good bonuses and a high salary?

The main two types of jobs

Revenue GeneratorsSupporting Cast

Employees that are directly involved in generating revenue or profit for the organization. Their field of expertise usually matches the type of business.

Employees that support and facilitate the work of revenue generators. Their expertise is usually different from that of the core business operations.

A graphics designer working for a graphics designing company.

A graphic designer in the marketing department of a hospital.

Revenue generators usually get more and higher bonuses, higher salaries, and more frequent salary increments. The reason is quite simple: it is easier to quantify your value to the company in monetary terms when you participate in revenue generation.

“Try to work for companies where your skills can generate revenue. We can&#;t all generate revenue and that&#;s perfectly fine.”

Bonus Comparison by Seniority Level

Top management personnel and senior employees naturally exhibit higher bonus rates and frequencies than juniors. This is very predictable due to the inherent responsibilities of being higher in the hierarchy. People in top positions can easily get double or triple bonus rates than employees down the pyramid.

Data Scientist Average Hourly Wage in Australia

70AUD per hour

The average hourly wage (pay per hour) in Australia is 70 AUD. This means that the average Data Scientist in Australia earns approximately 70 AUD for every worked hour.

Hourly Wage = Annual Salary &# ( 52 x 5 x 8 )

The hourly wage is the salary paid in one worked hour. Usually jobs are classified into two categories: salaried jobs and hourly jobs. Salaried jobs pay a fix amount regardless of the hours worked. Hourly jobs pay per worked hour. To convert salary into hourly wage the above formula is used (assuming 5 working days in a week and 8 working hours per day which is the standard for most jobs). The hourly wage calculation may differ slightly depending on the worked hours per week and the annual vacation allowance. The figures mentioned above are good approximations and are considered to be the standard. One major difference between salaried employees and hourly paid employees is overtime eligibility. Salaried employees are usually exempt from overtime as opposed to hourly paid staff.

Data Scientist VS Other Jobs

Salary Comparison Between Data Scientist and Science and Technical Services yearly Australia
Share This Chart  Tweet      Get Chart Link

The average salary for Data Scientist is 20% more than that of Science and Technical Services. Also, Science and Technical Services salaries are 34% more than those of All Jobs.

Salary comparison with similar jobs

3D Lab Technologist88, AUD%
Algorithm Developer, AUD%
Analytical Chemist, AUD+15%
Anthropologist, AUD%
Archeologist, AUD%
Assistant Breeder62, AUD%
Astronomer, AUD+46%
Atmospheric and Space Scientist, AUD+11%
Behavior Analyst, AUD%
Behavior Intervention Specialist, AUD%
Biochemist, AUD+36%
Biofuels Processing Technician74, AUD%
Biofuels Production Manager, AUD-9%
Biologist, AUD+28%
Biomedical Scientist, AUD+41%
Biophysicist, AUD+31%
Chemical Engineer90, AUD%
Chemical Technologist91, AUD%
Chemist, AUD+21%
Chief Technologist, AUD+18%
Climate Change Analyst, AUD%
Clinical Laboratory Scientist, AUD+31%
Computer Scientist, AUD+6%
Conservation Scientist, AUD+8%
Data Scientist, AUD+0%
DNA Analyst, AUD+33%
Ecologist, AUD+3%
Economic Development Specialist, AUD+5%
Flavourist67, AUD%
Food Scientist, AUD%
Forensic Scientist, AUD+11%
Formulation Technologist74, AUD%
Fraud Investigator98, AUD%
Genomics Scientist, AUD+35%
Geographer, AUD%
Geographic Information Systems Technician69, AUD%
Geological Data Technician63, AUD%
Geological Technician83, AUD%
Geologist, AUD+8%
Geomatics Scientist, AUD+8%
Geophysical Data Technician61, AUD%
Geospatial Information Scientist and Technologist, AUD+1%
Hydrologist, AUD%
Industrial Ecologist, AUD-9%
Intelligence Analyst, AUD%
Knowledge Management Specialist93, AUD%
Laboratory Manager, AUD%
Laboratory Researcher90, AUD%
Laboratory Technician61, AUD%
Life Sciences Analyst, AUD-7%
Life Scientist, AUD+4%
Marine Architect, AUD%
Marine Biologist, AUD-4%
Marine Superintendent82, AUD%
Materials Analyst83, AUD%
Materials Scientist, AUD+1%
Mathematician, AUD+8%
Medical Scientist, AUD+45%
Metallurgist, AUD-9%
Meteorologist, AUD-7%
Microbiologist, AUD+38%
Natural Language Processing Researcher, AUD%
Natural Resource Specialist, AUD%
Natural Sciences Manager, AUD+28%
Nuclear Engineer, AUD+43%
Physical Scientist, AUD+12%
Physicist, AUD+32%
Political Scientist, AUD+0%
Polygraph Examiner52, AUD%
Polysomnographic Technologist91, AUD%
Product Development Scientist, AUD+10%
Quantitative Research Analyst, AUD-8%
Quantitative Researcher, AUD-7%
Radiation Protection Specialist, AUD%
Refrigeration Technician44, AUD%
Research Scientist, AUD-9%
Risk Safety Engineer89, AUD%
Scientific Photographer88, AUD%
Scientific Programmer, AUD%
Scientist, AUD-0%
Service Engineer91, AUD%
Service Technician61, AUD%
Social Science Research Assistant81, AUD%
Social Scientist, AUD+4%
Sociologist, AUD+2%
Soil Scientist, AUD%
Statistical Analyst90, AUD%
Statistical Assistant60, AUD%
Statistician, AUD-5%
Survey Analyst87, AUD%
Survey Researcher81, AUD%
Surveying and Mapping Technician51, AUD%
Team Leader, AUD%
Technical Manager, AUD-8%
Technical Officer60, AUD%
Technical Service Director, AUD+26%
Technical Services Regulatory Affairs Specialist84, AUD%
Technical Services Research and Development Manager, AUD+38%
Technical Services Research Coordinator, AUD%
Technician56, AUD%
Water Ecologist, AUD+11%
Wildlife Biologist, AUD-4%

Salary Comparison By City

Adelaide, AUD
Brisbane, AUD
Canberra-Queanbeyan, AUD
Gold Coast-Tweed, AUD
Gosford, AUD
Melbourne, AUD
Newcastle, AUD
Perth, AUD
Sunshine Coast, AUD
Sydney, AUD
Wollongong, AUD

Government vs Private Sector Salary Comparison

Where can you get paid more, working for a private company or for the government? Public sector employees in Australia earn 5% more than their private sector counterparts on average across all sectors.

Private Sector

88, AUD

Public Sector+5%

93, AUD

Percentage increase and decrease are relative to the previous value




Data Scientist - Average Salary

The average salary for a Data Scientist is AU$, per year (AU$8, per month), which is AU$39, (+58%) higher than the national average salary in Australia.
A Data Scientist can expect an average starting salary of AU$50, The highest salaries can exceed AU$,

Total compensation includes salary and bonus.




Base SalaryAU$50, - ,
BonusAU$2, - 25,
Total CompensationAU$52, - ,




Base SalaryAU$4, - 16,
BonusAU$ - 2,
Total CompensationAU$4, - 18,

Salary australia data scientist

How much does a Data Scientist/Analytics , Intermediate make in Australia? The average Data Scientist/Analytics , Intermediate salary in Australia is A$98, as of March 19, , but the range typically falls between A$69, and A$,. Salary ranges can vary widely depending on many important factors, including education, certifications, additional skills, the number of years you have spent in your profession. With more global market data that allows you to price your jobs around the world and compare job salaries across countries and cities on real-time compensation data, helps you to determine your exact pay target.

Data Scientist/Analytics , Intermediate Frequently Asked Questions in Australia

What is the salary range for a Data Scientist/Analytics , Intermediate in Australia? What is the average hourly rate?

The average salary for a Data Scientist/Analytics , Intermediate in Australia is A$98, per year. The salary range for a Data Scientist/Analytics , Intermediate is between A$69, and A$, While we are seeing hourly wages as high as A$49 and as low as A$34, the majority of Data Scientist/Analytics , Intermediates are currently paid an average of A$47 in Australia. The average salary pay range for a Data Scientist/Analytics , Intermediate can vary depending on specific skills, level of skill, location, education, and years of experience. The company size, industry, and location, and numbers of available job candidates may also affect salary offers. Salaries for a Data Scientist/Analytics , Intermediate in Australia can differ based on any or all of these varying factors. March 19,

Why should you negotiate salary for a Data Scientist/Analytics , Intermediate role? What are effective negotiation strategies?

Most hiring managers in Australia expect job candidates to negotiate salary. By doing this you will demonstrate that you are confident in your abilities and comfortable taking initiative which are traits that are beneficial for almost any role. You should try to negotiate the highest starting salary of the Data Scientist/Analytics , Intermediate position that you can in Australia. This starting salary of the Data Scientist/Analytics , Intermediate position will become the basis for all future increases while you are employed at the firm. A lower starting salary will result in smaller raises, even if the % increase is large, so try to maximize that starting base salary amount.

Once you have received an offer of the Data Scientist/Analytics , Intermediate position in Australia, ask for a little time to consider it. Research salary levels for the position so you will know what range of salary is applicable for your job and location. Emphasize any special skills, experience, certifications, or credentials that you have. Point out past accomplishments that will be useful in the role. Suggest a salary that is slightly higher than your target, this will give you room to negotiate a lower amount but still meet your needs. March 19,

How do you evaluate the advantages, opportunities, and salary for a Data Scientist/Analytics , Intermediate role located in large metropolitan city or in a small town?

Start your evaluation by defining the most important aspects of the job and the overall lifestyle you can expect based on the location. The higher salary range of a Data Scientist/Analytics , Intermediate in the Australia can be one of the reasons you are attracted to a position in a large city, but keep in mind that differences in the cost of living usually result in higher living expenses and less disposable income. a Data Scientist/Analytics , Intermediate job in a large city of the Australia may offer a more varied experience, and greater opportunities for career progression, but may require long commutes or extended work hours. A large city in the Australia also provides more opportunities for entertainment and other activities. On the other hand, a non-metro location may offer lower salaries and fewer opportunities but have more affordable living expenses, shorter commute times, and other advantages. Consider these factors before you decide which Data Scientist/Analytics , Intermediate job is right for you. March 19,

Last Update: March 19,

Data Scientist Salary in Australia 2021 - $100K starting salary?

You get out of bed and go to the shower, and there: For what, for whom, and why I cant. Why can't I love. I am sitting with my headphones tense, Teacher ", and this is such a vocal and instrumental ensemble.

You will also be interested:

No, grandmother, you don't need an enema!", Objected the granddaughter, "Give me a candle, put it in my ass and poop. " no. ", Grandma opened the cabinet where her medicines were kept, I can put a piece of soap in your ass if you think.

779 780 781 782 783