A comprehensive guide to 17 different Data Science Jobs

29 mins

Data science is one of the most demanding and high-paying jobs today. And in this article, we will be taking you through 17 different data science jobs that you can look for as a fresher and all the relevant information you would be needing regarding them. By the end of your reading, you will have a clear understanding of data science, its future and what are the different data science jobs that you can choose from. 

How to get into Data Science?

Getting a data science job is not that hard, you just require an undergraduate or a postgraduate degree for it. The good news is that you don’t need a specific degree to land your dream job. But having a degree in the following fields might help you to stay ahead of your competition:- 

  • Mathematics 
  • Statistics
  • Business information system
  • Economics 
  • And, Computer science 

As mentioned earlier, it is not specified that you need to have these degrees. Moreover, the rise in the online certification programs and courses has reduced their need even further, so even if you lack degrees in these fields, you still have a good chance.

Data science jobs are all about data, numbers, analytics and visual representation. So before you enter into this field, make sure you make yourself comfortable with numbers, tables, graphs and much more because you will be mostly dealing with them only but in huge amounts.

The following are the key skills that may help you in the process:- 

  • Statistics
  • Linear algebra
  • Calculus 
  • Programming 
  • Databases
  • Distributed computing 
  • Machine learning
  • Visualization

There are much more skills that you may need to master but these are the foundations. 

These are the top 10 companies where you might wish to get hired as a data scientist:-

  • Google
  • Meta 
  • Apple 
  • Amazon 
  • Walmart 
  • Quora 
  • Microsoft 
  • IBM
  • Capital one 
  • Accenture

Now let’s talk about the average salary of a data scientist. According to Glassdoor at the entry-level, data science jobs pay around $1,17,212 per year on an average. Indeed states that the average base salary of a data scientist is $1,25,082 per year. 

And these are the salaries that some of the top companies around the globe pays:

  • Google:  $152,856
  • Apple: $145,974
  • Twitter: $135,360
  • Facebook: $134,715
  • PayPal: $132,909
  • Airbnb: $127,852
  • Microsoft: $123,328

Career progression as a Data Scientist

Data science jobs have a vast variety of roles and jobs that you can choose from, but for the time being let’s just categorize them as junior-level data scientist, mid-level data scientist and senior-level data scientist. 

Junior level data scientist 

At the entry-level or let’s say at the junior level, you are not assigned a huge task and most data scientists have to work on their skills at this level. The roles that you may be assigned would be mostly regarding prototyping projects with the help of data visualizations or you may be developing scripts.

The most advanced task that you may expect at this stage might include everyday check-ins with a senior data scientist and assisting them in code reviews and learning their integration into existing systems, you might be building and deploying a model into production.

At this level you do not identify the task, rather you are given one on which you have to work.

At the junior level, the data science jobs include more learning procedures and producing tasks for the management or other stakeholders. 

Mid-level data scientist

After the experience of around one or two years, you might advance in your career to a mid-level data scientist, and by now you will be able to take up larger projects and more complex business problems. At this level, you won’t need much help from your seniors and you will also be contributing to the organization in a much more advanced way. 

Now, you will be able to create an entire ETL pipeline by yourself while using the same into your machine learning model. At this level, one more advancement that you would be having is the freedom to choose the project and having independent project management. 

Senior-level data scientist

After a long journey of around five to seven years, you may find yourself in a senior-level position in your data science job. Now, that you are at a senior level, your amount of skills and experience will speak for itself. 

The skills in which you would be having mastery include a high level of data accuracy, good data quality, understanding of project scope and how to prioritize applications of data science, you would also find yourself as a skilled mentor towards the juniors. 

As a senior, your level of efficiency will determine your value. A highly skilled data scientist can easily take on highly complex problems and craft their end-to-end solutions. Now they would do this either individually or in a team.

Different data science jobs to choose from for freshers

Here is a list of 17 data science jobs that a fresher may choose from:- 

1. Business Analyst

Also known as management analysts, business analysts analyzes the data given to them and help in formulating data-driven informed decisions to help in maximizing business effectiveness. A business analyst understands the working of the organization and the sector it works in and develops the functions, and services to meet the goals.

These are the key responsibilities of a business analyst:-

  • Communicating with internal and external stakeholders to understand their needs and formulating solutions and strategies for its improvement.
  • Deriving insights from data and using data modeling practices to analyze your findings and creating their solutions
  • Identify the growth opportunities and potential risks related to the suggestions you made.

To efficiently carry out the above responsibilities, these are the skills that may help you:-

  • Gathering, tracking and performance analysis metrics will be a key to the business analysis role
  • Good communication skills 
  • Excellent knowledge of data visualization tools such as Tableau, excel and Bi tools
  • Proficiency in programming languages such as SQL and python
  • You also need to be familiar with business analysis methods such as Agile Business Analysis, Six Sigma, or Rational Unified Process.
  • Keen interest in business and business development
  • Having a strong grasp on the industry needs and having good knowledge of it will also help you in a major way as different industries have different business needs and they require a different approach to be solved. 

Now let's discuss the salary that you can expect at the different levels as we have discussed above, the junior level, mid-level and senior level.

Junior Level- At the junior level or let's say at the entry-level you can expect an average paycheck of around $37,707 per annum.
Mid-level- After a couple of years of experience, a business analyst may earn $85,006 per annum on average.
Senior-level- When you would have gained good expertise over the work and have a better understanding of the role, then you can expect a paycheck of $144,511 per annum. 

2. Database Administrator

Database administration is an IT professional who has access to the organization’s data and their role is to make sure that the data is optimally stored. They also make sure that the software programs are well designed, managed and maintained. 

The key responsibilities of a Database Administrator (DBA) includes:-

  • Creation and maintenance of database standards and policies 
  • Database backup design and strategizing storage
  • In order to optimum utilization, a DBA may also have to administer database objects
  • Database housekeeping 
  • Management of database security and integrity 
  • Testing and modification of databases to ensure their operational reliability
  • DBA also has to monitor concurrency level, response times and transaction volumes

The following is the list of skills and you need to have to become an excellent database administrator:- 

  • You need to have problem-solving skills and you should be able to think in terms of algorithms 
  • Hands-on experience with SQL and SQL server tools. 
  • You should be flexible and adaptable with excellent organizational skills 
  • Strong command with SSAS, SSIS, and SSRS. 
  • Unix shell scripting and PowerShell skills 
  • You should be aware of the requirements of an IT department 
  • You should be able to understand rational and dimensional data  modeling 

Moving further let’s discuss the average salary expectations from a DBA on different levels of seniority:- 

Junior level- At the junior level, a DBA can expect a salary in the range of $23,701-$26,933 per annum, your pay range depends upon your skills, communication and knowledge.
Mid-level-  After a year or two as a DBA , the salary increment could be expected at the range of $37,707-$48,480 per annum, it is advisable to focus on learning and skills as much as possible to attain the maximum pay range. 
Senior-level- When a DBA has attained a good amount of experience and reaches the senior level then the expected paycheck may be $64,641 per annum,  or even higher than that.  

3. Machine learning Engineer

A machine learning engineer is an IT person whose job is to create and design AI algorithms. ML engineers are also responsible for assessing, analyzing and organizing large amounts of data, at the same time also executing tests they are also given the task of optimization of machine learning models and algorithms.

ML engineers are also a linking person between the data scientists whose focus is on statistical and model-building and the construction of machine learning and AI systems.

The following are the key responsibilities of a Machine Learning(ML) Engineer:-

  • Demonstration of an end-to-end understanding of applications which includes not the machine learning algorithms as well.
  • Building algorithms that are based on statistical modeling 
  • Building and learning machine learning solutions that must be scalable as well.
  • ML engineer performs statistical analysis and runs machine learning tests.
  • Supporting product managers and engineers in implementing machine learning in the project.
  • Selection of appropriate data sets and methods of representing data. 
  • Identifying patterns and forecasting unseen instances using data modeling and evaluations strategy
  • Application of ML algorithms
  • Collaboration with data engineers and building data and model pipelines.

The skills that may come in handy for you to perform the above roles in the best way possible are the following:-

  • Bayesian statistics and advanced mathematics and statistical skills in subjects such as linear algebra and calculus.
  • Data modeling, data structure and data set understanding
  • Excellent knowledge of machine learning frameworks like keras, Pytorch as well as libraries like scikit-learn. 
  • Excellent analytical skills and highly attentive to details
  • Coding ability in Python, Java and R 
  • An ML engineer should be able to explain complex things to people who are not into programming

Now let's discuss the expected salary range of an ML engineer at different levels of experience:- 

Junior level- As a fresher ML engineers can expect a salary of around $37,741 per annum. 
Mid-level- After reaching the mid level the expected salary can be $56,073 per annum
Senior-level- At the senior level of their career, ML engineer earns up to $183,317 per annum if they work for some big MNCs such as Google or Facebook. 

4. Data Analyst

Data analysts are the ones who analyze the data, find insights and interpret it in order to solve problems. Data analysts are very high in demand in industries such as finance, medicine, criminal justice and business. 

These are the roles and responsibilities of a data analyst:-

  • Gathering, understanding and documentation of detailed business requirements with correct business tools and methods.
  • Data dashboard creation and visualization.
  • Maintaining automatic data processes. 
  • Designing database structure
  • Presenting the insights gathered from the data. 
  • Data quality monitoring and auditing. 
  • Identification, evaluation and implementation of external services and tools to support validation of data and its cleansing. 
  • Report preparation for executive leadership. 
  • Interpreting trends, patterns or forecasts with the help of relevant data.

The relevant skill set of a proficient data analyst are:-

  • To be an excellent data analyst, you need to get comfortable with numbers, data and strong analytical skills. 
  • Data modeling, data cleansing and data enrichment techniques. 
  • Excellent knowledge of tools such as Tableau, Microsoft excel. Power bi. R. SQL, Jupyter notebooks
  • Ability to visualize and represent the data to management in the best-understood way possible 
  • Linkage, data quality control and validation. 
  • Statistical methodologies and data analysis techniques. 
  • Ability to develop and document data workflows.

The expected salary of a data analyst at different levels are as follows:- 

Junior level- At the entry level, the expected salary of a data analyst may range from $24,801-$26,958 per annum. 
Mid-level- After gaining enough experience and knowledge in this field, the salary increment can be expected in the range of $32,350-$37,741 per annum
Senior-level- Once a certain amount of knowledge and expertise have been gathered, the salary hike can be expected to be higher than $64,700 per annum. 

5. Research Analyst

Employed mainly by asset management companies, a research analyst is a professional whose job is to recommend securities to money managers of the funds to make their investments. 

The job of a research analyst is divided into two sides, the buy-side and the sell-side. On the buy-side, they recommend buying securities and on the sell-side, their job is to recommend selling the securities. 

The roles and responsibilities given to a data analyst are as follows- 

  • Conducting research on different companies and forecasting the prices of their securities. 
  • Doing a fundamental and technical analysis of different sectors and companies if hired in finance. 
  • Development of pricing models 
  • Determining how promising certain investments might be for their clients
  • Identification of multibagger stocks for long term or short term. 

Skills required to be an excellent research analyst are as follows:- 

Masters degree in finance, economics or mathematics. Some companies may also expect the employee to pass at least CFA level-2

  • Familiarity with applied research and data management. 
  • Proficiency in excel and google sheets 
  • Strong mathematical and statistical skills 
  • Critical thinking ability and knowledge of finance
  • Able to do fundamental and technical analysis for a company, industry or sector. 
Salary expectations for a research analyst are as follows:-

Junior level- At the Entry-level a research analyst can expect a salary range of $62,400-$66,000 per annum
Mid-level- After some experience and expertise the salary may rise up to the range of $80,000-85,000 per annum. 
Senior-level- At the senior level of their field a research analyst may enjoy a salary between $95,000-$110,000 per annum. 

6. Cloud engineer

Cloud tech has become a part of everyone’s life now, almost everyone uses some sort of cloud-based service every day. Building and maintaining cloud infrastructure comes under the job of a cloud engineer. This role comes under the information technology(IT) sector

The key roles and responsibilities of a cloud engineer are as follows:- 

  • Migration of computer systems to cloud. 
  • Cloud data storage monitoring.
  • Modifications in the existing cloud data systems.
  • Development of cloud-based applications 
  • Automation of cloud based software throughout the company 
  • Client interactions, regarding cloud support and giving recommendations as per the clients’ needs, 
  • Crafting cloud operated database and software applications. 
  • Collaborating with engineers and identifying optimal cloud storage solutions 

The following are the skills that a company looks for in a cloud engineer:- 

  • Familiarity with CI/CD systems and SysOps. 
  • Knowledge SQL and NoSQL
  • Good grasp at developing software using programming languages such Python, JAVA, C++ or Ruby. 
  • Understanding of  API, REST and RPC. 
  • Proficiency in internet protocols such as TCP/IP, DNS, SMTP and HTTP. 
  • Experienced with software development, system engineering and open source technology
  • Azure, AWS and GCP certifications are preferred. 
The salaries and remuneration of a cloud engineer are as follows:- 

Junior level- Cloud engineers at the very base level or with little to no experience may expect a salary range of $75,500-$81,000 per annum. Here your awareness with the tech and the expertise matters and plays a crucial role in getting you a higher pay range. 
Mid-level- After a couple of years and a good grasp of the work the salary expectations may range somewhere between $90,000-$97,000 per annum. 
Senior-level- Once a cloud engineer completes more than 5 years in his/her role with sufficient knowledge and expertise then the pay range may be anywhere between $110,000-$123,00 per annum.  

7. Android developer 

Today a lot of people have an android smartphone, with the growing diversity of doable things, on a smartphone the demand of a person who is able to manage, develop and solve issues related to android operating softwares is also increasing. 

This is where an android developer comes into play. An android developer is also responsible for building different applications and software for android. 

The roles and responsibilities given to an android developer are as follows:- 

  • Code quality maintenance and automation
  • Improvement of application responsiveness and performance. 
  • Translating wireframes into high-quality code. 
  • Writing down codes for android based applications
  • Instrumentation test for codes and ensuring there best performance 
  • Designing and building high-performance JAVA codes with maximum efficiency 
  • Solving issues such as bottlenecks, bugs and ensuring the best performance of the applications 

The skills of an excellent android developer are as follows:- 

  • Proficiency in programming languages, UI/UX designing and mobile app platforms 
  • Excellent awareness of cyber security 
  • Agile development and backend computing 
  • Familiarity with web development languages like HTML5 and CSS. 
  • Excellency in eXtensible markup language, JAVA and Kotlin 
  • Ability to handle Database structure and algorithms 
  • Other soft skills like critical thinking, problem solving, good communication. 

The salaries that an android developer earns at different levels of their roles are as follows:- 

Junior level- At the junior level or entry-level, an android developer earns around $72,500-$76,000 per annum. 
Mid-level- After completion of one or more than a year and developing sufficient knowledge the salary increment may range from $85,000-$95,000 per annum. 
Senior-level- Once the developer reaches a senior position with enough expertise, knowledge and skill set, the paycheck ranges from $110,000-$122,000 per annum.  

8. Data engineer

Data engineer is an IT position where the primary task is to prepare data for the analytical team. They create the database and are responsible for its architecture as well. They also support the data science teams in preparing data sets procedures. 

The responsibilities of a data engineer are as follows;- 

  • Helping the data science team in data mining, data modeling and data production. 
  • Collection of data and working on its architecture. 
  • Conducting industry-centric research to identify any issues that may hinder the growth of the business. 
  • Building algorithms and prototypes
  • Collaboration with the teams of data scientists on various projects. 
  • Data Model creation and identifying patterns 
  • Data aggregation and extracting historical insights from the data models. 
  • Data system and pipeline building. 
  • Complex data analysis and reporting 
  • Interpreting the trends and identifying the patterns 
  • Opportunity identification in order to acquire data. 

Here is a list of the skills that a data engineer must have to become job-ready:- 

  • Coding knowledge and understanding of languages such as, Python, JAVA, GOLANG, Ruby, SAS, MatLab etc. 
  • Ability to warehouse data using Panoply or Redshift. 
  • Understanding of database solutions such as SQL, although SQL is a widely used program but some companies may look for other tools as well, such as Cassandra or BigTable. 
  • Excellent knowledge in data analytics softwares such as Apache, MapReduce, Hive etc. 
  • Hands-on experience with amazon web services, kafka and hadoop. 
  • Other soft skills such as better interpersonal communication, team management etc are also crucial in a data engineer career. 
  • This skill is not asked by the company but having this will definitely help you in your career progression and growth, and the skill is excellent time management. 

The salary expectations in the data engineer career at different levels of seniority and experience are as follows:-

Junior level- At the entry of their career, a data engineer may earn in the range of $91,000-$95,000 per annum. At the entry-level, factors such as your education, certifications, knowledge and communication skills play a major role in landing your desired pay,
Mid level- After working for a certain number of years and gaining some knowledge and experience data engineers are paid within the payscale of $105,000-$115,000 per annum. 
Senior-level- On a senior level, i.e. after more than 5-6 years of experience, data engineer can expect remuneration ranging between $120,000-$128,000 per annum.

9. Artificial intelligence engineer

An artificial intelligence (A.I.) engineer is a person who works on building models and networks that works on artificial intelligence applications and software. Developing systems with the use of A.I. to maximize efficiency and improve performance. It is one of the most demanding data science jobs. 

The key roles and responsibilities of an A.I. engineer include the following:- 

  • Testing and deploying A.I. models 
  • Creation of APIs 
  • Writing advanced set of codes 
  • Working in collaboration with the data science teams 
  • Coordinating between the data science teams and business analytics teams 
  • Machine learning based viable product development. 
  • AI model development 
  • Building algorithms in order to receive inputs on different departments such as sales, purchases etc. 
  • Doing statistical analysis and explaining the results to support in essential decision-making for the organization. 
  • Deploying produced software using Modern software development methodologies. 

The skills that you need to master to land your dream position as an A,I, engineer are as follows:- 

  • Excellent knowledge in programing languages such as Python, C++, Julia, Shell, Javascript, R
  • Ability to create summary statistics for a datasets
  • Excellent graphical representation of data and visualization, 
  • Machine learning algorithm proficiency
  • Good knowledge of linear algebra, calculus and statistics. 
  • Profound theoretical and practical knowledge of advanced signal processing algorithms such as wavelets, sherlets, curvelets and bandlets
  • Strong expertise in applied math and algorithms 
  • Profound knowledge of R, Tableau and SAS for creating excellent neural network architecture. 
  • Salaries expectations for an A.I. engineer at different levels are as follows:- 

Junior level- As a fresher A.I. engineers can earn upto $82,000-$90,000 per annum. 
Mid level-  After certain years of experience at the mid level, the pay range is around $97,000-$105,000 per annum. 
Senior-level- After a good amount of knowledge and expertise, the pay range of a senior artificial intelligence engineer ranges somewhere between $110,000-$125,000 per annum.  

10. Python backend developer 

The programmers whose specializations are in writing web application logic. Python developers use python programming to develop, debug and implement application projects. 

The roles and responsibilities of a python backend developer include the following:- 

  • Connecting applications with 3rd party web services. 
  • Application integration to support front end developers. 
  • Remove bugs from the application in order to ensure low latency 
  • Ensuring server security and data protection. 
  • Data storage solution accommodation
  • Developing digital tools so that online traffic can be monitored.
  • Effective and scalable python coding. 
  • Data storage solution integration
  • Current software system enhancement.
  • Performance tuning and application automation
  • A.I. predictive model creation. 

The skills that may help you to successfully deliver the above responsibilities are as follows:- 

  • Fundamental knowledge and proficiency of core  Python, Django etc. 
  • Excellent database knowledge. 
  • Good grasp of object-relational mapping 
  • Good understanding of code packaging, release as well as deployment. 
  • Understanding of libraries like TensorFlow, Scikit learn etc. 
  • Familiarity with data visualization, statistics and data analytics. 
  • Able to debug and test for tools such as selenium. 
  • Proficiency in integrating database and various database sources into a unified system. 
  • Other soft skills are also required such as critical thinking, analytical skills, problem solving and project management skills. 

The salary expectations for the python developer role are as follows:- 

Junior level- At the entry-level with little to no experience, you can expect a salary range of around $67,000-$75,000 per annum. 
Mid level- After a couple of years with a good amount of experience salary expectations may rise up to the range of $82,000-$95,000 per annum. 
Senior-level- After numerous projects, and so much time as a python developer the salary range may be anywhere between $101,000-$115,000 per annum. 

11. IOS developer

All the applications and software that are on your Apple devices or the ones that you see at the app store, the programming professionals behind them are called an IOS developer. Their task is to design and develop software and applications for IOS-based devices. 

The key responsibilities of an IOS developer are as follows; 

  • Apple-based software designing and building. 
  • Bottleneck resolving and identifying issues with the applications, 
  • Collaborating with the design to define, design and come up with new features. 
  • Maximizing the quality, performance and efficiency of the application. 
  • Checking the robustness of the code which includes its usability and reliability. 
  • Discovering, evaluating and implementing new technologies so maximum effectiveness of the application can be achieved. 
  • Fixing the application bugs and continuously improving its performance. 
  • Application publication on the app store. 

The skill set that a recruiter looks for in an IOS developer are:- 

  • Fundamental understanding of objective-C, swift Cocoa Touch. 
  • Knowledge of RESTful APIs so that the IOS application can be connected with the backend services, 
  • UI/UX standards knowledge with other web technologies. 
  • Proficient in the full mobile development cycle. 
  • Understanding of Apple's design principle and guidelines for application interface. 
  • Experienced in continuous integration.
  • Performance tuning, threading and offline storage knowledge. 
  • Knowledge of code versioning tools such as Git, Mercurial or SVN. 

The salary expectations of an IOS developer are as follows:- 

Junior level- At an entry level, the pay range of an IOS developer may be anywhere around $79,000-$85,000 per annum. 
Mid-level- After the experience of a couple of years, an IOS developer maybe able to earn $97,000-$104,000 per annum. 
Senior-level- At a good senior level, an IOS developer can enjoy a salary ranging from $115,000-$125,000 per annum.  

12. Software engineer 

Creating and developing computer systems, software, and applications is what a software engineer is responsible for. Also known as software programmers, this is a well-known position in the field of data science jobs. 

Following are the roles and responsibilities that a software engineer is given:- 

  • Analyzing requirements of the user and creating technical specifications according to them. 
  • System maintenance, their monitoring and removing software defects. 
  • Code writing and testing. 
  • Consultation with other staff members such as, engineer, security specialists, and internal and external stakeholders. 
  • Making collaborations with programmers to design and develop new software and maximize the efficiency of the current ones. 
  • System performance determination and recommending equipment environmental control. 
  • Information analysis and recommending computer specification, and layout equipment modification.                    

The skills that a software engineer must have are the following:- 

  • Excellent understanding of computer systems and their technologies. 
  • Excellency in analyzing complex problems and solving them.
  • Stronghold of computer programs such as  JavaScript, Linux/Unix, Perl, Shell etc. 
  • Good proficiency and fundamental understanding of PHP, Python, Hands-On SQL, Microsoft ASP.NET MVC, Web API and Node.js. 
  • Hands-on experience of C++, C# and C. 
  • Fundamental understanding of data structures, computer architecture, operating systems
  • Ability to work with source code and version repository. 

Now let's discuss the remuneration structure and range of this role at different levels of seniority:- 

Junior level- At the entry level as a fresher,, you can expect a salary of around $19,465 per annum. 
Mid-level- After you have an experience of a couple of years, the remuneration that you can expect would lie somewhere around $27,035-$54,070 per annum. At this level, your efficiency and work ethic would be a strong factor in determining your pay. 
Senior-level- After several years of experience and handling numerous computer systems and completing of various projects, at the senior level, you can expect a salary range of around $64,884-$75,698 per annum. 

13. Research engineer

Working within the Research and Development(       R&D) department of a company, as the name suggests, the job of a research engineer is to develop computer software and applications for the organization. Their job is somewhat the same as that of a software engineer, but the difference is that they are also indulged in the research part for a specific product. 

The roles and responsibilities that a research engineer is given are the following:- 

  • Doing research and finding out solutions for the company. 
  • Building industry-relevant software and systems and maximizing their functionality. 
  • Developing new computer software and updating the existing ones to maximize their efficiency, productivity and working. 
  • Ensuring responsiveness of the system products and their effectiveness. 
  • Idea development for further investigation, designing and experimenting those ideas. 
  • Technical information collection. 
  • Project planning related to the softwares and tracking their key results. 
  • Supporting engineering teams, scientist teams and technician teams. 

The skills that are required for a research designer are as follows:- 

  • Research skills and team management skills. 
  • Stronghold in analytics and design
  • Excellent problem-solving skills with a logical approach. 
  • Algebra and calculus skills. 

Other than these soft skills, the technical and tools mastery needed are the same as that of a software engineer. 

Now let's discuss the pay scale of a research engineer at different levels of experience:- 

Junior level- At the entry-level, a junior research engineer can expect a salary in the range of $38,500-$47,900 per annum. 
Mid-level- After some experience and knowledge, a research engineer can expect a salary somewhere within the range of $65,000-$78,000 per annum. 
Senior-level- When you reach a good position in your career and you have developed strong expertise and experience in your role, you can expect a salary range of around $89,000-$106,000 per annum.  

14. Statistician

A statistician is a mathematician, who uses his/her analytical and mathematics skill analyze the market trend, identify the data pattern, observe different data structures and extract conclusion from them to support in business planning and decision making, 

A role as a statistician is an important role for organizations and has a wide variety in the area of data science jobs. 

The roles and responsibilities of a statistician are as follows:- 

  • Problem identification and laying out plans and procedures to solve them. 
  • Understanding the patterns and trends in data to support the management in making decisions.
  • Data collection, analysis and interpretation to concerned stakeholders. 
  • Sample technique application to determine and define group surveys. 
  • Applying statistical methods and procedures to evaluate the validity of the data obtained. 
  • Strategizing and structuring plans to help the organization to reach its business goals. 
  • Drawing out the conclusions from the data collection and communicating them to the authorities. 

Here are the different skills that a statistician must possess to carry out their roles and responsibilities effectively and efficiently:- 

  • Hypothesis testing understanding and summary statistics knowledge. 
  • Good analytical skills and ability to identify the trends in the data patterns. 
  • R and SAS proficiency. 
  • Stronghold of programming languages such as  Python, C/C++, Java and Perl. 
  • Cloud computing and NoSQL knowledge. 
  • Fundamental understanding of Hadoop-based analytics. 
  • Team management and motivational skills to support the team. 
  • Decisive and able to solve complex problems. 
  • Excellent communication and presentation skills. 
  • Critical thinking and comfortable with numbers. 

Now we will discuss the salary range of a statistician which is as follows:- 

Junior level- At the fresher level with no or little amount of experience, a statistician can earn upto $57,500-$66,000 per annum. 
Mid-level- After a couple of years, as you progress in your career you can enjoy a salary range of somewhere between $75,000-$83,000 per annum. One thing that you need to remember at this point is that you may be able to earn even higher than this range if you develop a strong understanding of your work and the level of skill expertise also matters a lot. 
Senior-level- Once you have gained a good amount of knowledge and expertise in your role and after handling numerous projects, you can earn a handsome amount within the range of $97,000-$112,000 per annum.  

15. People Analyst

This role is mainly related to the HR department. The job is at a strategic level to gather data and use the insights to support the decision-making. The primary concern of this role is with the internal stakeholders of the organization and mainly the employees and staff. 

But one thing to remember is that this role may be related to HR but it does not fall under the category of HR division. It is still a part of data science jobs

The key roles and responsibilities of a people analyst are the following:- 

  • Selecting the database to use. 
  • Executing multivariate data analysis. 
  • Supporting  HR to carry out decision making and helping them to identify the best course of action. 
  • Consultation to people’s issues through an analytical approach. 
  • Problem-solving through qualitative and quantitative research design. 
  • Data sets identification and execution its alignment to wider organizational goals. 

The skills that may come in handy while performing the above roles and responsibilities are:- 

  • Profound knowledge and familiarity with the work of aN HR. 
  • Strong analytical skills and ability to solve complex and most peculiar problems. 
  • Strong business acumen. 
  • Proficiency in tools such as Tableau, ChartHop and visier. 
  • Ability to make data-driven decisions
  • Strong communication skills and ability to identify the patterns within the data sets. 

The salary structure of a people analyst is as follows:- 

Junior level- At the entry-level a people analyst may earn somewhere around $35,000-$48,000 per annum. 
Mid-level- After a couple of years of experience, you may earn a salary that ranges around $60,000-$75,000 per annum.
Senior-level- Once you are at a senior position in your role, the salary expectation would be on a scale of around $86,000-$98,000 per annum.  

16. Deep learning Engineer

These are the computer scientists who specialize in using deep learning techniques for specific tasks which include programming. Data modeling, data engineering and its deployment are a few tasks that are carried out by them. Primarily they are dealing with neural networks. 

This job is considered a subset of machine learning but is a critical part today in different roles in data science jobs. 

The roles and responsibilities of a deep learning engineer are as follows:- 

  • Selecting correct data sets and ensuring the data quality. 
  • Building and developing deep learning systems. 
  • Creating data science prototypes. 
  • Working with algorithms and ensuring maximum efficiency and also maximizing the qualitative factors of the data structures. 
  • Statistical analysis and data modeling. 
  • Deploying data sets and data models. 
  • Understanding the needs of clients and building deep learning applications and software in accordance with those needs. 
  • Tracking out differences in data distribution that may affect the performance of the data models built, 
  • Assisting the Machine learning engineers in developing ML software and applications.

The final task does not fall under the primary roles of a deep learning engineer and is assigned in very rare circumstances. 

The skills that the companies look for in a person while hiring are as follows:- 

  • Very strong hold in applied mathematics and algorithmic coding. 
  • Ability to create models using packages such as NumPy, scikit-learn, pandas, matplotlib, TensorFlow, and PyTorch. 
  • Proficiency in cloud engineering tools such as AWS, Azure and GCP. 
  • Familiarity with integrated development environments such as Jupyter Notebook and Sublime. 
  • Understanding of data structures and software architectures. 
  • Quick adaptability with changing technologies and software. 

The salary structure of a deep learning engineer is as follows:- 

Junior level- At the entry-level of your job, you can expect a salary range of $80,000-$92,000 per annum. 
Mid-level- After some experience, the salary increment can be within the range of $105,000-$117,000 per annum. 
Senior level- At the senior level, i.e. after the work experience of around 7+ years, the salary expectations can be anywhere between $122,000-130,000 per annum.  

17. Fraud Analyst

With the growing usage of online transactions around the globe, the amount of fraud on the internet is also increasing at a rapid pace. And this is where a fraud analyst comes to play. In the criminal investigation industry, this is one of the most demanding positions.

But some businesses also hire these professionals to ensure data security and avoid any theft or other issue. 

The roles and responsibilities of a fraud analyst are as follows:- 

  • Detection of potential fraud across their servers. 
  • Tracking the fraud source. 
  • Documenting the steps, and procedures used in solving a case. 
  • Executing Continuous data security checks and updating security measures wherever necessary. 
  • Maintaining the privacy of data and avoiding potential risks. 
  • Updating database security systems on a regular basis. 
  • Identifying the culprit behind an occurred fraud. 
  • Spreading awareness across the organization regarding data security and educating it to non-technical people. 
  • Consulting managers and helping them in taking appropriate measure and steps to do in case of data fraud. 

To perform the above roles and responsibilities effectively the following are the skills that you will need:- 

  • Advance computer skills and technological skills. 
  • Ability to identify the weakness within the system in the shortest span of time possible. 
  • Ability to communicate technical jargons to non technical in the most effective and efficient manner. 
  • Investigative ability to track down the issues. 
  • Ability to work with large data sets. 
  • Proficient knowledge of data analysis and synthesis. 
  • Competent skills in SQL
  • Stress management skills
  • Excellent communication skills 
  • Quick decision-making ability 

Now we will discuss the salary structure of a fraud analyst at different levels of their work:- 

Junior level- At the entry-level, a fresh fraud analyst can earn anywhere between $45,000-$56,000 per annum. 
Mid-level- At this level, you can expect a pay range of around $65,000-$78,000 per annum. 
Senior-level- After acquiring a good amount of experience and knowledge in your work, and considering other factors such as skills, the number of projects and the complexity of cases, a senior fraud analyst can expect a pay scale of $91,000-$110,000 per annum.  


Now that you have got an understanding of the different roles and careers in the field of data science. You can move ahead to brush up on those paths and launch yourself with your desired role from the data science jobs mentioned above. 

Before leaving here are a few things that you should consider before choosing your career path:

  • Never ever choose a career or a role just on the basis of the salary, identify what you truly love and enjoy doing, that is what would help you boost ahead quickly. 
  • Always try to learn new skills related to your role wherever possible, this will keep you ahead of your others and give you a competitive edge. 
  • As you would have noticed above just hard technical skills are not necessary, you need to work upon your soft skills as well to land your dream job. 
  • Whatever field you are going to pursue,  make sure you develop the necessary portfolio related to your role, this will ensure that you have practical knowledge as well. 
  • Work on as many projects as possible to gain the necessary knowledge and skills. 

Data science is a field that is growing at a very rapid pace and to get your dream data science job, you need to grow your skill set and yourself at the same pace. 


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